Parameterizing Phrase Based Statistical Machine Translation Models: An Analytic Study

ERIC Educational Resources Information Center

Cer, Daniel

2011-01-01

The goal of this dissertation is to determine the best way to train a statistical machine translation system. I first develop a state-of-the-art machine translation system called Phrasal and then use it to examine a wide variety of potential learning algorithms and optimization criteria and arrive at two very surprising results. First, despite the…

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…

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…

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…

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

PubMed

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

2018-02-22

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

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…

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.

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

PubMed

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

2016-01-01

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

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…

English to Sanskrit Machine Translation Using Transfer Based approach

NASA Astrophysics Data System (ADS)

Pathak, Ganesh R.; Godse, Sachin P.

2010-11-01

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

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

ERIC Educational Resources Information Center

Madkour, Magda

2016-01-01

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

Chunk Alignment for Corpus-Based Machine Translation

ERIC Educational Resources Information Center

Kim, Jae Dong

2011-01-01

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

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…

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

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

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.

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…

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.

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.

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.

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,…

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.

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…

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

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.

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…

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…

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.

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.

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…

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)

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…

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

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

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

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,…

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…

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

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…

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

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

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

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

NASA Astrophysics Data System (ADS)

Sasayama, Manabu; Kuroiwa, Shingo; Ren, Fuji

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

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.

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…

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.

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

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,…

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.

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…

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.

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

Learning molecular energies using localized graph kernels.

PubMed

Ferré, Grégoire; Haut, Terry; Barros, Kipton

2017-03-21

Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

Learning molecular energies using localized graph kernels

NASA Astrophysics Data System (ADS)

Ferré, Grégoire; Haut, Terry; Barros, Kipton

2017-03-01

Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

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

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…

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.

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

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

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.

Learning molecular energies using localized graph kernels

DOE PAGES

Ferré, Grégoire; Haut, Terry Scot; Barros, Kipton Marcos

2017-03-21

We report that recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturallymore » incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. Finally, we benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.« less

Learning molecular energies using localized graph kernels

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

Ferré, Grégoire; Haut, Terry Scot; Barros, Kipton Marcos

We report that recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturallymore » incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. Finally, we benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.« less

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

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"…

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.

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.

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…

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.

Some Problems in German to English Machine Translation

DTIC Science & Technology

1974-12-01

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

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.

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.

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 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

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

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

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…

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…

Towards Automatically Aligning German Compounds with English Word Groups in an Example-Based Translation System.

ERIC Educational Resources Information Center

Jones, Daniel; Alexa, Melina

As part of the development of a completely sub-symbolic machine translation system, a method for automatically identifying German compounds was developed. Given a parallel bilingual corpus, German compounds are identified along with their English word groupings by statistical processing alone. The underlying principles and the design process are…

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.

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

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

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.

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…

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.

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.

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.

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.

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

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

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-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

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.

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.

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.

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.

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)

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

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.

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.

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).

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.

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.

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.

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

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.

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.

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.

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)

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)

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.

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.

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.

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.

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.

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.

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.

Electrophoretic Deformation of Individual Transfer RNA Molecules Reveals Their Identity.

PubMed

Henley, Robert Y; Ashcroft, Brian Alan; Farrell, Ian; Cooperman, Barry S; Lindsay, Stuart M; Wanunu, Meni

2016-01-13

It has been hypothesized that the ribosome gains additional fidelity during protein translation by probing structural differences in tRNA species. We measure the translocation kinetics of different tRNA species through ∼3 nm diameter synthetic nanopores. Each tRNA species varies in the time scale with which it is deformed from equilibrium, as in the translocation step of protein translation. Using machine-learning algorithms, we can differentiate among five tRNA species, analyze the ratios of tRNA binary mixtures, and distinguish tRNA isoacceptors.

A Grammar Library for Information Structure

ERIC Educational Resources Information Center

Song, Sanghoun

2014-01-01

This dissertation makes substantial contributions to both the theoretical and computational treatment of information structure, with an eye toward creating natural language processing applications such as multilingual machine translation systems. The aim of the present dissertation is to create a grammar library of information structure for the…

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

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.

Industrial machine systems risk assessment: a critical review of concepts and methods.

PubMed

Etherton, John R

2007-02-01

Reducing the risk of work-related death and injury to machine operators and maintenance personnel poses a continuing occupational safety challenge. The risk of injury from machinery in U.S. workplaces is high. Between 1992 and 2001, there were, on average, 520 fatalities per year involving machines and, on average, 3.8 cases per 10,000 workers of nonfatal caught-in-running-machine injuries involving lost workdays. A U.S. task group recently developed a technical reference guideline, ANSI B11 TR3, "A Guide to Estimate, Evaluate, & Reduce Risks Associated with Machine Tools," that is intended to bring machine tool risk assessment practice in the United States up to or above the level now required by the international standard, ISO 14121. The ANSI guideline emphasizes identifying tasks and hazards not previously considered, particularly those associated with maintenance; and it further emphasizes teamwork among line workers, engineers, and safety professionals. The value of this critical review of concepts and methods resides in (1) its linking current risk theory to machine system risk assessment and (2) its exploration of how various risk estimation tools translate into risk-informed decisions on industrial machine system design and use. The review was undertaken to set the stage for a field evaluation study on machine risk assessment among users of the ANSI B11 TR3 method.

Translating an AI application from Lisp to Ada: A case study

NASA Technical Reports Server (NTRS)

Davis, Gloria J.

1991-01-01

A set of benchmarks was developed to test the performance of a newly designed computer executing both Lisp and Ada. Among these was AutoClassII -- a large Artificial Intelligence (AI) application written in Common Lisp. The extraction of a representative subset of this complex application was aided by a Lisp Code Analyzer (LCA). The LCA enabled rapid analysis of the code, putting it in a concise and functionally readable form. An equivalent benchmark was created in Ada through manual translation of the Lisp version. A comparison of the execution results of both programs across a variety of compiler-machine combinations indicate that line-by-line translation coupled with analysis of the initial code can produce relatively efficient and reusable target code.

Translations on Eastern Europe Scientific Affairs, Number 560

DTIC Science & Technology

1977-10-04

Miklos Szilagyi . TAPNEG; prepares digitalized printed wiring diagram control punch tape on an ADMAP-2 graphing machine with reflection on the x axis...FOKAL 16 KE; BME, Dr Zsolt Illyefalvi-Vitez; BME, Dr Miklos Szilagyi . TESTOP-10; the program provides measurement and diagnostics for logic cards

Natural Language Processing: Toward Large-Scale, Robust Systems.

ERIC Educational Resources Information Center

Haas, Stephanie W.

1996-01-01

Natural language processing (NLP) is concerned with getting computers to do useful things with natural language. Major applications include machine translation, text generation, information retrieval, and natural language interfaces. Reviews important developments since 1987 that have led to advances in NLP; current NLP applications; and problems…

A Novel Approach to Creating Disambiguated Multilingual Dictionaries

ERIC Educational Resources Information Center

Boguslavsky, Igor; Cardenosa, Jesus; Gallardo, Carolina

2009-01-01

Multilingual lexicons are needed in various applications, such as cross-lingual information retrieval, machine translation, and some others. Often, these applications suffer from the ambiguity of dictionary items, especially when an intermediate natural language is involved in the process of the dictionary construction, since this language adds…

Konnen Computer das Sprachproblem losen (Can Computers Solve the Language Problem)?

ERIC Educational Resources Information Center

Zeilinger, Michael

1972-01-01

Various computer applications in linguistics, primarily speech synthesis and machine translation, are reviewed. Although the computer proves useful for statistics, dictionary building and programmed instruction, the promulgation of a world auxiliary language is considered a more human and practical solution to the international communication…

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.

University of Maryland walking robot: A design project for undergraduate students

NASA Technical Reports Server (NTRS)

Olsen, Bob; Bielec, Jim; Hartsig, Dave; Oliva, Mani; Grotheer, Phil; Hekmat, Morad; Russell, David; Tavakoli, Hossein; Young, Gary; Nave, Tom

1990-01-01

The design and construction required that the walking robot machine be capable of completing a number of tasks including walking in a straight line, turning to change direction, and maneuvering over an obstable 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 the machine about this support. The machine can be controlled by using either a user operated remote tether or the on-board computer for the execution of control commands. Absolute encoders are attached to all motors (leg, main drive, and Bigfoot) to provide the control computer with information regarding the status of the motors (up-down motion, forward or reverse rotation). Long and short range infrared sensors provide the computer with feedback information regarding the machine's relative position to a series of stripes and reflectors. These infrared sensors simulate how the robot might sense and gain information about the environment of Mars.

Dependency Structures for Statistical Machine Translation

ERIC Educational Resources Information Center

Bach, Nguyen

2012-01-01

Dependency structures represent a sentence as a set of dependency relations. Normally the dependency structures from a tree connect all the words in a sentence. One of the most defining characters of dependency structures is the ability to bring long distance dependency between words to local dependency structures. Another the main attraction of…

Application of Social Network Analysis Techniques to Machine Translated Documents

DTIC Science & Technology

2010-04-01

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

Sensory Aids for the Blind.

ERIC Educational Resources Information Center

National Academy of Sciences - National Research Council, Washington, DC. Committee on Prosthetics Research and Development.

The problems of providing sensory aids for the blind are presented and a report on the present status of aids discusses direct translation and recognition reading machines as well as mobility aids. Aspects of required research considered are the following: assessment of needs; vision, audition, taction, and multimodal communication; reading aids,…

An Operational System for Subject Switching between Controlled Vocabularies: A Computational Linguistics Approach.

ERIC Educational Resources Information Center

Silvester, June P.; And Others

This report describes a new automated process that pioneers full-scale operational use of subject switching by the NASA (National Aeronautics and Space Administration) Scientific and Technical Information (STI) Facility. The subject switching process routinely translates machine-readable subject terms from one controlled vocabulary into the…

Temporal Sequences Quantify the Contributions of Individual Fixations in Complex Perceptual Matching Tasks

ERIC Educational Resources Information Center

Busey, Thomas; Yu, Chen; Wyatte, Dean; Vanderkolk, John

2013-01-01

Perceptual tasks such as object matching, mammogram interpretation, mental rotation, and satellite imagery change detection often require the assignment of correspondences to fuse information across views. We apply techniques developed for machine translation to the gaze data recorded from a complex perceptual matching task modeled after…

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.

An information-carrying and knowledge-producing molecular machine. A Monte-Carlo simulation.

PubMed

Kuhn, Christoph

2012-02-01

The concept called Knowledge is a measure of the quality of genetically transferred information. Its usefulness is demonstrated quantitatively in a Monte-Carlo simulation on critical steps in a origin of life model. The model describes the origin of a bio-like genetic apparatus by a long sequence of physical-chemical steps: it starts with the presence of a self-replicating oligomer and a specifically structured environment in time and space that allow for the formation of aggregates such as assembler-hairpins-devices and, at a later stage, an assembler-hairpins-enzyme device-a first translation machine.

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

PubMed

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

2015-08-13

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

Fast femtosecond laser ablation for efficient cutting of sintered alumina substrates

NASA Astrophysics Data System (ADS)

Oosterbeek, Reece N.; Ward, Thomas; Ashforth, Simon; Bodley, Owen; Rodda, Andrew E.; Simpson, M. Cather

2016-09-01

Fast, accurate cutting of technical ceramics is a significant technological challenge because of these materials' typical high mechanical strength and thermal resistance. Femtosecond pulsed lasers offer significant promise for meeting this challenge. Femtosecond pulses can machine nearly any material with small kerf and little to no collateral damage to the surrounding material. The main drawback to femtosecond laser machining of ceramics is slow processing speed. In this work we report on the improvement of femtosecond laser cutting of sintered alumina substrates through optimisation of laser processing parameters. The femtosecond laser ablation thresholds for sintered alumina were measured using the diagonal scan method. Incubation effects were found to fit a defect accumulation model, with Fth,1=6.0 J/cm2 (±0.3) and Fth,∞=2.5 J/cm2 (±0.2). The focal length and depth, laser power, number of passes, and material translation speed were optimised for ablation speed and high quality. Optimal conditions of 500 mW power, 100 mm focal length, 2000 μm/s material translation speed, with 14 passes, produced complete cutting of the alumina substrate at an overall processing speed of 143 μm/s - more than 4 times faster than the maximum reported overall processing speed previously achieved by Wang et al. [1]. This process significantly increases processing speeds of alumina substrates, thereby reducing costs, making femtosecond laser machining a more viable option for industrial users.

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.

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.

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.

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.

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.

Effect of Dimension and Shape of Magnet on the Performance AC Generator with Translation Motion

NASA Astrophysics Data System (ADS)

Indriani, A.; Dimas, S.; Hendra

2018-02-01

The development of power plants using the renewable energy sources is very rapid. Renewable energy sources used solar energy, wind energy, ocean wave energy and other energy. All of these renewable energy sources require a processing device or a change of motion system to become electrical energy. One processing device is a generator which have work principle of converting motion (mechanical) energy into electrical energy with rotary shaft, blade and other motion components. Generator consists of several types of rotation motion and linear motion (translational). The generator have components such as rotor, stator and anchor. In the rotor and stator having magnet and winding coil as an electric generating part of the electric motion force. Working principle of AC generator with linear motion (translation) also apply the principle of Faraday that is using magnetic induction which change iron magnet to produce magnetic flux. Magnetic flux is captured by the stator to be converted into electrical energy. Linear motion generators consist of linear induction machine, wound synchronous machine field, and permanent magnet synchronous [1]. Performance of synchronous generator of translation motion is influenced by magnet type, magnetic shape, coil winding, magnetic and coil spacing and others. In this paper focus on the neodymium magnet with varying shapes, number of coil windings and gap of magnetic distances. This generator work by using pneumatic mechanism (PLTGL) for power plants system. Result testing of performance AC generator translation motion obtained that maximum voltage, current and power are 63 Volt for diameter winding coil 0.15 mm, number of winding coil 13000 and distance of magnet 20 mm. For effect shape of magnet, maximum voltage happen on rectangle magnet 30x20x5 mm with 4.64 Volt. Voltage and power on effect of diameter winding coil is 14.63 V and 17.82 W at the diameter winding coil 0.7 and number of winding coil is 1260 with the distance of magnet 25 mm.

Actes des Journees de linguistique (Proceedings of the Linguistics Conference) (9th, 1995).

ERIC Educational Resources Information Center

Audette, Julie, Ed.; And Others

Papers (entirely in French) presented at the conference on linguistics include these topics: language used in the legislature of New Brunswick; cohesion in the text of Arabic-speaking language learners; automatic adverb recognition; logic of machine translation in teaching revision; expansion in physics texts; discourse analysis and the syntax of…

ELNET--The Electronic Library Database System.

ERIC Educational Resources Information Center

King, Shirley V.

1991-01-01

ELNET (Electronic Library Network), a Japanese language database, allows searching of index terms and free text terms from articles and stores the full text of the articles on an optical disc system. Users can order fax copies of the text from the optical disc. This article also explains online searching and discusses machine translation. (LRW)

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.

Translingual Fine-Grained Morphosyntactic Analysis and Its Application to Machine Translation

ERIC Educational Resources Information Center

Drabek, Elliott Franco

2009-01-01

English and a small set of other languages have a wealth of available linguistic knowledge resources and annotated language data, but the great majority of the world's languages have little or none. This dissertation describes work which leverages the detailed and accurate morphosyntactic analyses available for English to improve analytical…

Automated implementation of rule-based expert systems with neural networks for time-critical applications

NASA Technical Reports Server (NTRS)

Ramamoorthy, P. A.; Huang, Song; Govind, Girish

1991-01-01

In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

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.

Fluctuations in protein synthesis from a single RNA template: stochastic kinetics of ribosomes.

PubMed

Garai, Ashok; Chowdhury, Debashish; Ramakrishnan, T V

2009-01-01

Proteins are polymerized by cyclic machines called ribosomes, which use their messenger RNA (mRNA) track also as the corresponding template, and the process is called translation. We explore, in depth and detail, the stochastic nature of the translation. We compute various distributions associated with the translation process; one of them--namely, the dwell time distribution--has been measured in recent single-ribosome experiments. The form of the distribution, which fits best with our simulation data, is consistent with that extracted from the experimental data. For our computations, we use a model that captures both the mechanochemistry of each individual ribosome and their steric interactions. We also demonstrate the effects of the sequence inhomogeneities of real genes on the fluctuations and noise in translation. Finally, inspired by recent advances in the experimental techniques of manipulating single ribosomes, we make theoretical predictions on the force-velocity relation for individual ribosomes. In principle, all our predictions can be tested by carrying out in vitro experiments.

Programming and Tuning a Quantum Annealing Device to Solve Real World Problems

NASA Astrophysics Data System (ADS)

Perdomo-Ortiz, Alejandro; O'Gorman, Bryan; Fluegemann, Joseph; Smelyanskiy, Vadim

2015-03-01

Solving real-world applications with quantum algorithms requires overcoming several challenges, ranging from translating the computational problem at hand to the quantum-machine language to tuning parameters of the quantum algorithm that have a significant impact on the performance of the device. In this talk, we discuss these challenges, strategies developed to enhance performance, and also a more efficient implementation of several applications. Although we will focus on applications of interest to NASA's Quantum Artificial Intelligence Laboratory, the methods and concepts presented here apply to a broader family of hard discrete optimization problems, including those that occur in many machine-learning algorithms.

Advances in natural language processing.

PubMed

Hirschberg, Julia; Manning, Christopher D

2015-07-17

Natural language processing employs computational techniques for the purpose of learning, understanding, and producing human language content. Early computational approaches to language research focused on automating the analysis of the linguistic structure of language and developing basic technologies such as machine translation, speech recognition, and speech synthesis. Today's researchers refine and make use of such tools in real-world applications, creating spoken dialogue systems and speech-to-speech translation engines, mining social media for information about health or finance, and identifying sentiment and emotion toward products and services. We describe successes and challenges in this rapidly advancing area. Copyright © 2015, American Association for the Advancement of Science.

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.

Using Linguistic Knowledge in Statistical Machine Translation

DTIC Science & Technology

2010-09-01

on newswire test data . . . . . . . . . . . . . . . . . . . . . 65 3.4 Arabic to English MT results for Arabic morphological segmentation, measured on...web test data. . . . . . . . . . . . . . . . . . . . . . . . 65 3.5 Recombination Results. Percentage of sentences with mis-combined words...scores for syntactic reordering of the Spoken Language Domain. 90 5.1 Normalized likelihood of the test set alignments without decision trees, and then

Software Independent Verification and Validation (SIV&V) Simplified

DTIC Science & Technology

2006-12-01

Configuration Item I/O Input/Output I2V2 Independent Integrated Verification and Validation IBM International Business Machines ICD Interface...IPT Integrated Product Team IRS Interface Requirements Specification ISD Integrated System Diagram ITD Integrated Test Description ITP ...programming languages such as COBOL (Common Business Oriented Language) (Codasyl committee 1960), and FORTRAN (FORmula TRANslator) ( IBM 1952) (Robat 11

The Visual Uncertainty Paradigm for Controlling Screen-Space Information in Visualization

ERIC Educational Resources Information Center

Dasgupta, Aritra

2012-01-01

The information visualization pipeline serves as a lossy communication channel for presentation of data on a screen-space of limited resolution. The lossy communication is not just a machine-only phenomenon due to information loss caused by translation of data, but also a reflection of the degree to which the human user can comprehend visual…

State-based verification of RTCP-nets with nuXmv

NASA Astrophysics Data System (ADS)

Biernacka, Agnieszka; Biernacki, Jerzy; Szpyrka, Marcin

2015-12-01

The paper deals with an algorithm of translation of RTCP-nets' (real-time coloured Petri nets) coverability graphs into nuXmv state machines. The approach enables users to verify RTCP-nets with model checking techniques provided by the nuXmv tool. Full details of the algorithm are presented and an illustrative example of the approach usefulness is provided.

Finding Relevant Data in a Sea of Languages

DTIC Science & Technology

2016-04-26

full machine-translated text , unbiased word clouds , query-biased word clouds , and query-biased sentence...and information retrieval to automate language processing tasks so that the limited number of linguists available for analyzing text and spoken...the crime (stock market). The Cross-LAnguage Search Engine (CLASE) has already preprocessed the documents, extracting text to identify the language

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

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.

Automated document analysis system

NASA Astrophysics Data System (ADS)

Black, Jeffrey D.; Dietzel, Robert; Hartnett, David

2002-08-01

A software application has been developed to aid law enforcement and government intelligence gathering organizations in the translation and analysis of foreign language documents with potential intelligence content. The Automated Document Analysis System (ADAS) provides the capability to search (data or text mine) documents in English and the most commonly encountered foreign languages, including Arabic. Hardcopy documents are scanned by a high-speed scanner and are optical character recognized (OCR). Documents obtained in an electronic format bypass the OCR and are copied directly to a working directory. For translation and analysis, the script and the language of the documents are first determined. If the document is not in English, the document is machine translated to English. The documents are searched for keywords and key features in either the native language or translated English. The user can quickly review the document to determine if it has any intelligence content and whether detailed, verbatim human translation is required. The documents and document content are cataloged for potential future analysis. The system allows non-linguists to evaluate foreign language documents and allows for the quick analysis of a large quantity of documents. All document processing can be performed manually or automatically on a single document or a batch of documents.

Performance evaluation of various classifiers for color prediction of rice paddy plant leaf

NASA Astrophysics Data System (ADS)

Singh, Amandeep; Singh, Maninder Lal

2016-11-01

The food industry is one of the industries that uses machine vision for a nondestructive quality evaluation of the produce. These quality measuring systems and softwares are precalculated on the basis of various image-processing algorithms which generally use a particular type of classifier. These classifiers play a vital role in making the algorithms so intelligent that it can contribute its best while performing the said quality evaluations by translating the human perception into machine vision and hence machine learning. The crop of interest is rice, and the color of this crop indicates the health status of the plant. An enormous number of classifiers are available to solve the purpose of color prediction, but choosing the best among them is the focus of this paper. Performance of a total of 60 classifiers has been analyzed from the application point of view, and the results have been discussed. The motivation comes from the idea of providing a set of classifiers with excellent performance and implementing them on a single algorithm for the improvement of machine vision learning and, hence, associated applications.

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.

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.

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

Information Sciences Assessment for Asia and Australasia

DTIC Science & Technology

2009-10-16

entertainment and home services - Machine Translation for international cooperation - NLU + Affective Computing for education - Intelligent Optimization for...into an emotion. ETTS, embedded Mandarin, music retrieval. Also, research in areas of computer graphics, digital media processing  Intelligent...many from outside China, 40% in phase 2 Sales volume in 2007 130 * 100 million RMB SAP (1st), CITI, AIG, EDS, Capgemini, ILOG, Infosys, HCL, Sony

Computer-Aided Transcription in the Courts. Executive Summary. National Center Publication No. R-0058.

ERIC Educational Resources Information Center

National Center for State Courts, Williamsburg, VA.

This report summarizes the findings of the Computer-Aided Transcription (CAT) Project, which conducted a 14-month study of the technology and use of computer systems for translating into English the shorthand notes taken by court reporters on stenotype machines. Included are the state of the art of CAT at the end of 1980 and anticipated future…

Speech Processing and Recognition (SPaRe)

DTIC Science & Technology

2011-01-01

results in the areas of automatic speech recognition (ASR), speech processing, machine translation (MT), natural language processing ( NLP ), and...Processing ( NLP ), Information Retrieval (IR) 16. SECURITY CLASSIFICATION OF: UNCLASSIFED 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME...Figure 9, the IOC was only expected to provide document submission and search; automatic speech recognition (ASR) for English, Spanish, Arabic , and

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…

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

Impact of Machine-Translated Text on Entity and Relationship Extraction

DTIC Science & Technology

2014-12-01

20 1 1. Introduction Using social network analysis tools is an important asset in...semantic modeling software to automatically build detailed network models from unstructured text. Contour imports unstructured text and then maps the text...onto an existing ontology of frames at the sentence level, using FrameNet, a structured language model, and through Semantic Role Labeling ( SRL

Articles on Practical Cybernetics. Computer-Developed Computers; Heuristics and Modern Sciences; Linguistics and Practice; Cybernetics and Moral-Ethical Considerations; and Men and Machines at the Chessboard.

ERIC Educational Resources Information Center

Berg, A. I.; And Others

Five articles which were selected from a Russian language book on cybernetics and then translated are presented here. They deal with the topics of: computer-developed computers, heuristics and modern sciences, linguistics and practice, cybernetics and moral-ethical considerations, and computer chess programs. (Author/JY)

Software Testbed for Developing and Evaluating Integrated Autonomous Systems

DTIC Science & Technology

2015-03-01

EUROPA planning system for plan generation. The adaptive controller executes the new plan, using augmented, hierarchical finite state machines to...using the Internet Communications Engine ( ICE ), an object-oriented toolkit for building distributed applications. TABLE OF CONTENTS 1...ANML model is translated into the New Domain Definition Language (NDDL) and sent to NASA???s EUROPA planning system for plan generation. The adaptive

The Writing of Chinese Characters by CFL Learners: Can Writing on Facebook and Using Machine Translation Help?

ERIC Educational Resources Information Center

Zhang, Qi; Lu, Zhouxiang

2014-01-01

The current study investigates the applications of the pinyin input system, a Chinese word processing method, for writing on Facebook in order to help CFL (Chinese as a foreign language) learners from two Irish universities to improve their handwriting in Chinese characters on paper. The data were collected from writing activities conducted over…

A Semisupervised Support Vector Machines Algorithm for BCI Systems

PubMed Central

Qin, Jianzhao; Li, Yuanqing; Sun, Wei

2007-01-01

As an emerging technology, brain-computer interfaces (BCIs) bring us new communication interfaces which translate brain activities into control signals for devices like computers, robots, and so forth. In this study, we propose a semisupervised support vector machine (SVM) algorithm for brain-computer interface (BCI) systems, aiming at reducing the time-consuming training process. In this algorithm, we apply a semisupervised SVM for translating the features extracted from the electrical recordings of brain into control signals. This SVM classifier is built from a small labeled data set and a large unlabeled data set. Meanwhile, to reduce the time for training semisupervised SVM, we propose a batch-mode incremental learning method, which can also be easily applied to the online BCI systems. Additionally, it is suggested in many studies that common spatial pattern (CSP) is very effective in discriminating two different brain states. However, CSP needs a sufficient labeled data set. In order to overcome the drawback of CSP, we suggest a two-stage feature extraction method for the semisupervised learning algorithm. We apply our algorithm to two BCI experimental data sets. The offline data analysis results demonstrate the effectiveness of our algorithm. PMID:18368141

A coordination theory for intelligent machines

NASA Technical Reports Server (NTRS)

Wang, Fei-Yue; Saridis, George N.

1990-01-01

A formal model for the coordination level of intelligent machines is established. The framework of the coordination level investigated consists of one dispatcher and a number of coordinators. The model called coordination structure has been used to describe analytically the information structure and information flow for the coordination activities in the coordination level. Specifically, the coordination structure offers a formalism to (1) describe the task translation of the dispatcher and coordinators; (2) represent the individual process within the dispatcher and coordinators; (3) specify the cooperation and connection among the dispatcher and coordinators; (4) perform the process analysis and evaluation; and (5) provide a control and communication mechanism for the real-time monitor or simulation of the coordination process. A simple procedure for the task scheduling in the coordination structure is presented. The task translation is achieved by a stochastic learning algorithm. The learning process is measured with entropy and its convergence is guaranteed. Finally, a case study of the coordination structure with three coordinators and one dispatcher for a simple intelligent manipulator system illustrates the proposed model and the simulation of the task processes performed on the model verifies the soundness of the theory.

TOOTHPASTEV6.11.3

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

Sankel, David J.; Clair, Aaron B. St.; Langsfield, Joshua D.

2006-11-01

Toothpaste is a graphical user interface and Computer Aided Drafting/Manufacturing (CAD/CAM) software package used to plan tool paths for Galil Motion Control hardware. The software is a tool for computer controlled dispensing of materials. The software may be used for solid freeform fabrication of components or the precision printing of inks. Mathematical calculations are used to produce a set of segments and arcs that when coupled together will fill space. The paths of the segments and arcs are then translated into a machine language that controls the motion of motors and translational stages to produce tool paths in three dimensions.more » As motion begins material(s) are dispensed or printed along the three-dimensional pathway.« less

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

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Investigation of roughing machining simulation by using visual basic programming in NX CAM system

NASA Astrophysics Data System (ADS)

Hafiz Mohamad, Mohamad; Nafis Osman Zahid, Muhammed

2018-03-01

This paper outlines a simulation study to investigate the characteristic of roughing machining simulation in 4th axis milling processes by utilizing visual basic programming in NX CAM systems. The selection and optimization of cutting orientation in rough milling operation is critical in 4th axis machining. The main purpose of roughing operation is to approximately shape the machined parts into finished form by removing the bulk of material from workpieces. In this paper, the simulations are executed by manipulating a set of different cutting orientation to generate estimated volume removed from the machine parts. The cutting orientation with high volume removal is denoted as an optimum value and chosen to execute a roughing operation. In order to run the simulation, customized software is developed to assist the routines. Operations build-up instructions in NX CAM interface are translated into programming codes via advanced tool available in the Visual Basic Studio. The codes is customized and equipped with decision making tools to run and control the simulations. It permits the integration with any independent program files to execute specific operations. This paper aims to discuss about the simulation program and identifies optimum cutting orientations for roughing processes. The output of this study will broaden up the simulation routines performed in NX CAM systems.

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

Compiler writing system detail design specification. Volume 2: Component specification

NASA Technical Reports Server (NTRS)

Arthur, W. J.

1974-01-01

The logic modules and data structures composing the Meta-translator module are desribed. This module is responsible for the actual generation of the executable language compiler as a function of the input Meta-language. Machine definitions are also processed and are placed as encoded data on the compiler library data file. The transformation of intermediate language in target language object text is described.

Evaluating SPLASH-2 Applications Using MapReduce

NASA Astrophysics Data System (ADS)

Zhu, Shengkai; Xiao, Zhiwei; Chen, Haibo; Chen, Rong; Zhang, Weihua; Zang, Binyu

MapReduce has been prevalent for running data-parallel applications. By hiding other non-functionality parts such as parallelism, fault tolerance and load balance from programmers, MapReduce significantly simplifies the programming of large clusters. Due to the mentioned features of MapReduce above, researchers have also explored the use of MapReduce on other application domains, such as machine learning, textual retrieval and statistical translation, among others.

Deep Gate Recurrent Neural Network

DTIC Science & Technology

2016-11-22

Schmidhuber. A system for robotic heart surgery that learns to tie knots using recurrent neural networks. In IEEE International Conference on...tasks, such as Machine Translation (Bahdanau et al. (2015)) or Robot Reinforcement Learning (Bakker (2001)). The main idea behind these networks is to...and J. Peters. Reinforcement learning in robotics : A survey. The International Journal of Robotics Research, 32:1238–1274, 2013. ISSN 0278-3649. doi

Toward Determining the Comprehensibility of Machine Translations

DTIC Science & Technology

2012-01-01

responses to a stimulus (Macmillan and Creelman , 1991). It has been applied in areas such as lie detection (truth/lie), inspection (ac- ceptable...1-1/(2N) (Macmil- lan and Creelman , 1991). Negative values, which usually indicate response confusion, were eliminated. The results of...Macmillan, Neil and C. Douglas Creelman . (1991). Detection theory: A User’s guide. Cambridge Univer- sity Press, pp. 10 &125. Marchant

Radioactive hot cell access hole decontamination machine

DOEpatents

Simpson, William E.

1982-01-01

Radioactive hot cell access hole decontamination machine. A mobile housing has an opening large enough to encircle the access hole and has a shielding door, with a door opening and closing mechanism, for uncovering and covering the opening. The housing contains a shaft which has an apparatus for rotating the shaft and a device for independently translating the shaft from the housing through the opening and access hole into the hot cell chamber. A properly sized cylindrical pig containing wire brushes and cloth or other disks, with an arrangement for releasably attaching it to the end of the shaft, circumferentially cleans the access hole wall of radioactive contamination and thereafter detaches from the shaft to fall into the hot cell chamber.

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.

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

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

A Formal Model of Ambiguity and its Applications in Machine Translation

DTIC Science & Technology

2010-01-01

structure indicates linguisti- cally implausible segmentation that might be generated using dictionary - driven approaches...derivation. As was done in the monolingual case, the functions LHS, RHSi, RHSo and υ can be extended to a derivation δ. D(q) where q ∈V denotes the... monolingual parses. My algorithm runs more efficiently than O(n6) with many grammars (including those that required using heuristic search with other parsers

Parsing and Tagging of Bilingual Dictionary

DTIC Science & Technology

2003-09-01

LAMP-TR-106 CAR-TR-991 CS-TR-4529 UMIACS-TR-2003-97 PARSING ANS TAGGING OF BILINGUAL DICTIONARY Huanfeng Ma1,2, Burcu Karagol-Ayan1,2, David... dictionaries hold great potential as a source of lexical resources for training and testing automated systems for optical character recognition, machine...translation, and cross-language information retrieval. In this paper, we describe a system for extracting term lexicons from printed bilingual dictionaries

Translations on USSR Science and Technology Physical Sciences and Technology No. 7

DTIC Science & Technology

1977-02-28

cybernetics. [Answer] Immediately after the war , when the restoration of the national economy, which had been wrecked by the enemy, was started, Soviet...cyberneticization of economics and science will be developed at accelerated rates. 8545 CSO: 1870 CYBERNETICS, COMPUTERS AND AUTOMATION TECHNOLOGY...working storage of the machine exceeds 64 thousand alpha-numeric characters. Communication with the external world is effected by means of a main

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

Predicting Mouse Liver Microsomal Stability with “Pruned” Machine Learning Models and Public Data

PubMed Central

Perryman, Alexander L.; Stratton, Thomas P.; Ekins, Sean; Freundlich, Joel S.

2015-01-01

Purpose Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Methods Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). Results “Pruning” out the moderately unstable/moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 hour. Conclusions Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources. PMID:26415647

Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data.

PubMed

Perryman, Alexander L; Stratton, Thomas P; Ekins, Sean; Freundlich, Joel S

2016-02-01

Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). "Pruning" out the moderately unstable / moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 h. Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources.

Wireless Cortical Brain-Machine Interface for Whole-Body Navigation in Primates

NASA Astrophysics Data System (ADS)

Rajangam, Sankaranarayani; Tseng, Po-He; Yin, Allen; Lehew, Gary; Schwarz, David; Lebedev, Mikhail A.; Nicolelis, Miguel A. L.

2016-03-01

Several groups have developed brain-machine-interfaces (BMIs) that allow primates to use cortical activity to control artificial limbs. Yet, it remains unknown whether cortical ensembles could represent the kinematics of whole-body navigation and be used to operate a BMI that moves a wheelchair continuously in space. Here we show that rhesus monkeys can learn to navigate a robotic wheelchair, using their cortical activity as the main control signal. Two monkeys were chronically implanted with multichannel microelectrode arrays that allowed wireless recordings from ensembles of premotor and sensorimotor cortical neurons. Initially, while monkeys remained seated in the robotic wheelchair, passive navigation was employed to train a linear decoder to extract 2D wheelchair kinematics from cortical activity. Next, monkeys employed the wireless BMI to translate their cortical activity into the robotic wheelchair’s translational and rotational velocities. Over time, monkeys improved their ability to navigate the wheelchair toward the location of a grape reward. The navigation was enacted by populations of cortical neurons tuned to whole-body displacement. During practice with the apparatus, we also noticed the presence of a cortical representation of the distance to reward location. These results demonstrate that intracranial BMIs could restore whole-body mobility to severely paralyzed patients in the future.

Compact Microscope Imaging System with Intelligent Controls

NASA Technical Reports Server (NTRS)

McDowell, Mark

2004-01-01

The figure presents selected views of a compact microscope imaging system (CMIS) that includes a miniature video microscope, a Cartesian robot (a computer- controlled three-dimensional translation stage), and machine-vision and control subsystems. The CMIS was built from commercial off-the-shelf instrumentation, computer hardware and software, and custom machine-vision software. The machine-vision and control subsystems include adaptive neural networks that afford a measure of artificial intelligence. The CMIS can perform several automated tasks with accuracy and repeatability . tasks that, heretofore, have required the full attention of human technicians using relatively bulky conventional microscopes. In addition, the automation and control capabilities of the system inherently include a capability for remote control. Unlike human technicians, the CMIS is not at risk of becoming fatigued or distracted: theoretically, it can perform continuously at the level of the best human technicians. In its capabilities for remote control and for relieving human technicians of tedious routine tasks, the CMIS is expected to be especially useful in biomedical research, materials science, inspection of parts on industrial production lines, and space science. The CMIS can automatically focus on and scan a microscope sample, find areas of interest, record the resulting images, and analyze images from multiple samples simultaneously. Automatic focusing is an iterative process: The translation stage is used to move the microscope along its optical axis in a succession of coarse, medium, and fine steps. A fast Fourier transform (FFT) of the image is computed at each step, and the FFT is analyzed for its spatial-frequency content. The microscope position that results in the greatest dispersal of FFT content toward high spatial frequencies (indicating that the image shows the greatest amount of detail) is deemed to be the focal position.

Ten-dimensional anthropomorphic arm control in a human brain-machine interface: difficulties, solutions, and limitations

NASA Astrophysics Data System (ADS)

Wodlinger, B.; Downey, J. E.; Tyler-Kabara, E. C.; Schwartz, A. B.; Boninger, M. L.; Collinger, J. L.

2015-02-01

Objective. In a previous study we demonstrated continuous translation, orientation and one-dimensional grasping control of a prosthetic limb (seven degrees of freedom) by a human subject with tetraplegia using a brain-machine interface (BMI). The current study, in the same subject, immediately followed the previous work and expanded the scope of the control signal by also extracting hand-shape commands from the two 96-channel intracortical electrode arrays implanted in the subject’s left motor cortex. Approach. Four new control signals, dictating prosthetic hand shape, replaced the one-dimensional grasping in the previous study, allowing the subject to control the prosthetic limb with ten degrees of freedom (three-dimensional (3D) translation, 3D orientation, four-dimensional hand shaping) simultaneously. Main results. Robust neural tuning to hand shaping was found, leading to ten-dimensional (10D) performance well above chance levels in all tests. Neural unit preferred directions were broadly distributed through the 10D space, with the majority of units significantly tuned to all ten dimensions, instead of being restricted to isolated domains (e.g. translation, orientation or hand shape). The addition of hand shaping emphasized object-interaction behavior. A fundamental component of BMIs is the calibration used to associate neural activity to intended movement. We found that the presence of an object during calibration enhanced successful shaping of the prosthetic hand as it closed around the object during grasping. Significance. Our results show that individual motor cortical neurons encode many parameters of movement, that object interaction is an important factor when extracting these signals, and that high-dimensional operation of prosthetic devices can be achieved with simple decoding algorithms. ClinicalTrials.gov Identifier: NCT01364480.

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.

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

Making extreme computations possible with virtual machines

NASA Astrophysics Data System (ADS)

Reuter, J.; Chokoufe Nejad, B.; Ohl, T.

2016-10-01

State-of-the-art algorithms generate scattering amplitudes for high-energy physics at leading order for high-multiplicity processes as compiled code (in Fortran, C or C++). For complicated processes the size of these libraries can become tremendous (many GiB). We show that amplitudes can be translated to byte-code instructions, which even reduce the size by one order of magnitude. The byte-code is interpreted by a Virtual Machine with runtimes comparable to compiled code and a better scaling with additional legs. We study the properties of this algorithm, as an extension of the Optimizing Matrix Element Generator (O'Mega). The bytecode matrix elements are available as alternative input for the event generator WHIZARD. The bytecode interpreter can be implemented very compactly, which will help with a future implementation on massively parallel GPUs.

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.

A multi-frame soft x-ray pinhole imaging diagnostic for single-shot applicationsa)

NASA Astrophysics Data System (ADS)

Wurden, G. A.; Coffey, S. K.

2012-10-01

For high energy density magnetized target fusion experiments at the Air Force Research Laboratory FRCHX machine, obtaining multi-frame soft x-ray images of the field reversed configuration (FRC) plasma as it is being compressed will provide useful dynamics and symmetry information. However, vacuum hardware will be destroyed during the implosion. We have designed a simple in-vacuum pinhole nosecone attachment, fitting onto a Conflat window, coated with 3.2 mg/cm2 of P-47 phosphor, and covered with a thin 50-nm aluminum reflective overcoat, lens-coupled to a multi-frame Hadland Ultra intensified digital camera. We compare visible and soft x-ray axial images of translating (˜200 eV) plasmas in the FRX-L and FRCHX machines in Los Alamos and Albuquerque.

LOOP IIId of the HCV IRES is essential for the structural rearrangement of the 40S-HCV IRES complex

PubMed Central

Angulo, Jenniffer; Ulryck, Nathalie; Deforges, Jules; Chamond, Nathalie; Lopez-Lastra, Marcelo; Masquida, Benoît; Sargueil, Bruno

2016-01-01

As obligatory intracellular parasites, viruses rely on cellular machines to complete their life cycle, and most importantly they recruit the host ribosomes to translate their mRNA. The Hepatitis C viral mRNA initiates translation by directly binding the 40S ribosomal subunit in such a way that the initiation codon is correctly positioned in the P site of the ribosome. Such a property is likely to be central for many viruses, therefore the description of host-pathogen interaction at the molecular level is instrumental to provide new therapeutic targets. In this study, we monitored the 40S ribosomal subunit and the viral RNA structural rearrangement induced upon the formation of the binary complex. We further took advantage of an IRES viral mutant mRNA deficient for translation to identify the interactions necessary to promote translation. Using a combination of structure probing in solution and molecular modeling we establish a whole atom model which appears to be very similar to the one obtained recently by cryoEM. Our model brings new information on the complex, and most importantly reveals some structural rearrangement within the ribosome. This study suggests that the formation of a ‘kissing complex’ between the viral RNA and the 18S ribosomal RNA locks the 40S ribosomal subunit in a conformation proficient for translation. PMID:26626152

Assessment of the information content of patterns: an algorithm

NASA Astrophysics Data System (ADS)

Daemi, M. Farhang; Beurle, R. L.

1991-12-01

A preliminary investigation confirmed the possibility of assessing the translational and rotational information content of simple artificial images. The calculation is tedious, and for more realistic patterns it is essential to implement the method on a computer. This paper describes an algorithm developed for this purpose which confirms the results of the preliminary investigation. Use of the algorithm facilitates much more comprehensive analysis of the combined effect of continuous rotation and fine translation, and paves the way for analysis of more realistic patterns. Owing to the volume of calculation involved in these algorithms, extensive computing facilities were necessary. The major part of the work was carried out using an ICL 3900 series mainframe computer as well as other powerful workstations such as a RISC architecture MIPS machine.

Compiling global name-space programs for distributed execution

NASA Technical Reports Server (NTRS)

Koelbel, Charles; Mehrotra, Piyush

1990-01-01

Distributed memory machines do not provide hardware support for a global address space. Thus programmers are forced to partition the data across the memories of the architecture and use explicit message passing to communicate data between processors. The compiler support required to allow programmers to express their algorithms using a global name-space is examined. A general method is presented for analysis of a high level source program and along with its translation to a set of independently executing tasks communicating via messages. If the compiler has enough information, this translation can be carried out at compile-time. Otherwise run-time code is generated to implement the required data movement. The analysis required in both situations is described and the performance of the generated code on the Intel iPSC/2 is presented.

Molecular mimicry between protein and tRNA.

PubMed

Nakamura, Y

2001-01-01

Mimicry is a sophisticated development in animals, fish, and plants that allows them to fool others by imitating a shape or color for diverse purposes, such as to prey, evade, lure, pollinate, or threaten. This is not restricted to the macro-world, but extends to the micro-world as molecular mimicry. Recent advances in structural and molecular biology uncovered a set of translation factors that resembles a tRNA shape and, in one case, even mimics a tRNA function for deciphering the genetic code. Nature must have evolved this art of molecular mimicry between protein and ribonucleic acid by using different protein structures until the translation factors sat in the cockpit of a ribosome machine, on behalf of tRNA, and achieved diverse actions. Structural, functional, and evolutionary aspects of molecular mimicry will be discussed.

Precision Timed Infrastructure: Design Challenges

DTIC Science & Technology

2013-09-19

timing constructs Clock synchronization and communication PRET Machines Other Platforms Fig. 1. Conceptual overview of translation steps between...2002. [3] A. Benveniste and G. Berry. The Synchronous Approach to Reactive and Real- Time Systems. Proceedings of the IEEE, 79(9):1270–1282, 1991. [4] D...and E. Lee. A programming model for time - synchronized distributed real- time systems. In Real Time and Embedded Technology and Applications Symposium, 2007. RTAS’07. 13th IEEE, pages

Translations on USSR Science and Technology, Physical Sciences and Technology, Number 16

DTIC Science & Technology

1977-08-05

34INVESTIGATION OF SPLITTING OF LIGHT NUCLEI WITH HIGH-ENERGY y -RAYS WITH THE METHOD OF WILSON’S CHAMBER OPERATING IN POWERFUL BEAMS OF ELECTRONIC...boast high reliability, high speed, and extremely modest power requirements. Information oh the Screen Visual display devices greatly facilitate...area of application of these units Includes navigation, control of power systems, machine tools, and manufac- turing processes. Th» ^»abilities of

AGARD Flight Test Instrumentation Series. Volume 18. Microprocessor Applications in Airborne Flight Test Instrumentation

DTIC Science & Technology

1987-02-01

flowcharting . 3. ProEram Codin in HLL. This stage consists of transcribing the previously designed program into R an t at can be translated into the machine...specified conditios 7. Documentation. Program documentation is necessary for user information, for maintenance, and for future applications. Flowcharts ...particular CP U. Asynchronous. Operating without reference to an overall timing source. BASIC. Beginners ’ All-purpose Symbolic Instruction Code; a widely

Divergence Measures Tool:An Introduction with Brief Tutorial

DTIC Science & Technology

2014-03-01

in detecting differences across a wide range of Arabic -language text files (they varied by genre, domain, spelling variation, size, etc.), our...other. 2 These measures have been put to many uses in natural language processing ( NLP ). In the evaluation of machine translation (MT...files uploaded into the tool must be .txt files in ASCII or UTF-8 format. • This tool has been tested on English and Arabic script**, but should

Translations on USSR Science and Technology, Biomedical and Behavioral Sciences, Number 15

DTIC Science & Technology

1977-11-16

processed. By applying systems theory to synthesis of complex man-machine systems we form ergatic organisms which not only have external and internal...without exception (and this is extremely important to emphasize) as a complex , integral formation, which through various traditions has acquired a...and outputs of the whole, which has a complex internal organization and structure, which we can no longer ignore in our analysis. Thus analysis and

Translations on Environmental Quality, Number 129.

DTIC Science & Technology

1977-01-27

agricultural procedures have not led to acidity in rivers in other parts of the country with similar soil conditions. Finally, the leaders of the project...Rosenqvist’s report gives interesting points of view concerning the conditions in the soil and the acidic precipitation, but the report builds on a series...bones, eggshells and poultry skin, used tires, waste gasoline, used cardboard, machine and engine noise, gas stench and toxic sprays, were right away

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

JPRS report: Science and technology. Central Eurasia

NASA Astrophysics Data System (ADS)

1994-05-01

Translated articles cover the following topics: optimal systems to detect and classify moving objects; multiple identification of optical readings in multisensor information and measurement system; method of first integrals in synthesis of optimal control; study of the development of turbulence in the region of a break above a triangular wing; electroerosion machining in aviation engine construction; and cumulation of a flat shock wave in a tube by a thin parietal gas layer of lower density.

Good Applications for Crummy Machine Translation

DTIC Science & Technology

1991-07-01

number of rewriting rules for transfer and generation processes is around 800, and it will be increased in the coming few months. The dictionary ...this time to do other useful tasks), as well as the time for the second dictionary update (on the grounds that these new or modified entrie., are not...little more than provide word-processing functionality, dictionary access and so on, but as time goes on, one might imagine functionality that begins to

UMass at TREC 2002: Cross Language and Novelty Tracks

DTIC Science & Technology

2002-01-01

resources – stemmers, dictionaries , machine translation, and an acronym database. We found that proper names were extremely important in this year’s queries...data by manually annotating 48 additional topics. 1. Cross Language Track We submitted one monolingual run and four cross-language runs. For the... monolingual run, the technology was essentially the same as the system we used for TREC 2001. For the cross-language run, we integrated some new

Improving Domain-specific Machine Translation by Constraining the Language Model

DTIC Science & Technology

2012-07-01

performance. To make up for the lack of parallel training data, one assumption is that more monolingual target language data should be used in building the...target language model. Prior work on domain-specific MT has focused on training target language models with monolingual 2 domain-specific data...showed that the using a large dictionary extracted from medical domain documents in a statistical MT system to generalize the training data significantly

Good Applications for Crummy Machine Translation

DTIC Science & Technology

1993-01-01

for transfer and generation processes is around 800, and it will be increased in the coming few months. The dictionary contains about 16,000 items at...time to do other useful tasks), as well as the time for the second dictionary update (on the grounds that these new or modified entries are not intended...might do little more than provide word-processing functionality, dictionary access and so on, but as time goes on, one might imagine functionality

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.

When Machines Think: Radiology's Next Frontier.

PubMed

Dreyer, Keith J; Geis, J Raymond

2017-12-01

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

Machines first, humans second: on the importance of algorithmic interpretation of open chemistry data.

PubMed

Clark, Alex M; Williams, Antony J; Ekins, Sean

2015-01-01

The current rise in the use of open lab notebook techniques means that there are an increasing number of scientists who make chemical information freely and openly available to the entire community as a series of micropublications that are released shortly after the conclusion of each experiment. We propose that this trend be accompanied by a thorough examination of data sharing priorities. We argue that the most significant immediate benefactor of open data is in fact chemical algorithms, which are capable of absorbing vast quantities of data, and using it to present concise insights to working chemists, on a scale that could not be achieved by traditional publication methods. Making this goal practically achievable will require a paradigm shift in the way individual scientists translate their data into digital form, since most contemporary methods of data entry are designed for presentation to humans rather than consumption by machine learning algorithms. We discuss some of the complex issues involved in fixing current methods, as well as some of the immediate benefits that can be gained when open data is published correctly using unambiguous machine readable formats. Graphical AbstractLab notebook entries must target both visualisation by scientists and use by machine learning algorithms.

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.

Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: a critical review.

PubMed

Orrù, Graziella; Pettersson-Yeo, William; Marquand, Andre F; Sartori, Giuseppe; Mechelli, Andrea

2012-04-01

Standard univariate analysis of neuroimaging data has revealed a host of neuroanatomical and functional differences between healthy individuals and patients suffering a wide range of neurological and psychiatric disorders. Significant only at group level however these findings have had limited clinical translation, and recent attention has turned toward alternative forms of analysis, including Support-Vector-Machine (SVM). A type of machine learning, SVM allows categorisation of an individual's previously unseen data into a predefined group using a classification algorithm, developed on a training data set. In recent years, SVM has been successfully applied in the context of disease diagnosis, transition prediction and treatment prognosis, using both structural and functional neuroimaging data. Here we provide a brief overview of the method and review those studies that applied it to the investigation of Alzheimer's disease, schizophrenia, major depression, bipolar disorder, presymptomatic Huntington's disease, Parkinson's disease and autistic spectrum disorder. We conclude by discussing the main theoretical and practical challenges associated with the implementation of this method into the clinic and possible future directions. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

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

A multi-frame soft x-ray pinhole imaging diagnostic for single-shot applications

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

Wurden, G. A.; Coffey, S. K.

2012-10-15

For high energy density magnetized target fusion experiments at the Air Force Research Laboratory FRCHX machine, obtaining multi-frame soft x-ray images of the field reversed configuration (FRC) plasma as it is being compressed will provide useful dynamics and symmetry information. However, vacuum hardware will be destroyed during the implosion. We have designed a simple in-vacuum pinhole nosecone attachment, fitting onto a Conflat window, coated with 3.2 mg/cm{sup 2} of P-47 phosphor, and covered with a thin 50-nm aluminum reflective overcoat, lens-coupled to a multi-frame Hadland Ultra intensified digital camera. We compare visible and soft x-ray axial images of translating ({approx}200more » eV) plasmas in the FRX-L and FRCHX machines in Los Alamos and Albuquerque.« less

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

The NATO thesaurus project

NASA Technical Reports Server (NTRS)

Krueger, Jonathan

1990-01-01

This document describes functionality to be developed to support the NATO technical thesaurus. Described are the specificity of the thesaurus structure and function; the distinction between the thesaurus information and its representation in a given online, machine readable, or printed form; the enhancement of the thesaurus with the assignment of COSATI codes (fields and groups) to posting terms, the integration of DTIC DRIT and NASA thesauri related terminology, translation of posting terms into French; and the provision of a basis for system design.

(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

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

DTIC Science & Technology

2007-08-01

In this domain, queries typically show a deeply nested structure, which makes the semantic parsing task rather challenging , e.g.: What states border...only 80% of the GEOQUERY queries are semantically tractable, which shows that GEOQUERY is indeed a more challenging domain than ATIS. Note that none...a particularly challenging task, because of the inherent ambiguity of natural languages on both sides. It has inspired a large body of research. In

IFLA General Conference, 1991. Division of Special Libraries Services: Section of Social Science Libraries; Section of Geography and Map Libraries; Section of Biological and Medical Sciences Libraries; Section of Art Libraries. Booklet 2.

ERIC Educational Resources Information Center

International Federation of Library Associations and Institutions, The Hague (Netherlands).

The 10 papers in this booklet were presented at meetings of 4 sections within the Division of Special Libraries: (1) "Information Ensurance of a Scientist" (V. Matveyev, USSR); (2) "Linguistic Barriers and Machine Translation" (Stanley Kalkus, USA); (3) "Maps for Planning" (V. I. Zhukov and L. G. Rudenko, USSR); (4)…

Translations on Eastern Europe Political, Sociological, and Military Affairs No. 1467

DTIC Science & Technology

1977-11-01

and still does. *A group of a few teenagers, not a large group, has been working there for many years. The group was engaged in photography ...inclucating the Pupils’ Code? It may be that errors existed back at the very assumption of this didactic affair, which, it is true, is not producing...textile industry; with Yugoslavia--in the production of locomotive types, of lorries, of machine- tools , of medium tonnage cargoes. The Romanian-West

Research in speech communication.

PubMed

Flanagan, J

1995-10-24

Advances in digital speech processing are now supporting application and deployment of a variety of speech technologies for human/machine communication. In fact, new businesses are rapidly forming about these technologies. But these capabilities are of little use unless society can afford them. Happily, explosive advances in microelectronics over the past two decades have assured affordable access to this sophistication as well as to the underlying computing technology. The research challenges in speech processing remain in the traditionally identified areas of recognition, synthesis, and coding. These three areas have typically been addressed individually, often with significant isolation among the efforts. But they are all facets of the same fundamental issue--how to represent and quantify the information in the speech signal. This implies deeper understanding of the physics of speech production, the constraints that the conventions of language impose, and the mechanism for information processing in the auditory system. In ongoing research, therefore, we seek more accurate models of speech generation, better computational formulations of language, and realistic perceptual guides for speech processing--along with ways to coalesce the fundamental issues of recognition, synthesis, and coding. Successful solution will yield the long-sought dictation machine, high-quality synthesis from text, and the ultimate in low bit-rate transmission of speech. It will also open the door to language-translating telephony, where the synthetic foreign translation can be in the voice of the originating talker.

Affine Transform to Reform Pixel Coordinates of EOG Signals for Controlling Robot Manipulators Using Gaze Motions

PubMed Central

Rusydi, Muhammad Ilhamdi; Sasaki, Minoru; Ito, Satoshi

2014-01-01

Biosignals will play an important role in building communication between machines and humans. One of the types of biosignals that is widely used in neuroscience are electrooculography (EOG) signals. An EOG has a linear relationship with eye movement displacement. Experiments were performed to construct a gaze motion tracking method indicated by robot manipulator movements. Three operators looked at 24 target points displayed on a monitor that was 40 cm in front of them. Two channels (Ch1 and Ch2) produced EOG signals for every single eye movement. These signals were converted to pixel units by using the linear relationship between EOG signals and gaze motion distances. The conversion outcomes were actual pixel locations. An affine transform method is proposed to determine the shift of actual pixels to target pixels. This method consisted of sequences of five geometry processes, which are translation-1, rotation, translation-2, shear and dilatation. The accuracy was approximately 0.86° ± 0.67° in the horizontal direction and 0.54° ± 0.34° in the vertical. This system successfully tracked the gaze motions not only in direction, but also in distance. Using this system, three operators could operate a robot manipulator to point at some targets. This result shows that the method is reliable in building communication between humans and machines using EOGs. PMID:24919013

FRX-L Research Status and Plans

NASA Astrophysics Data System (ADS)

Wurden, G. A.; Intrator, T. P.; Taccetti, J. M.; Furno, I. G.; Hsu, S. C.; Zhang, S. Y.; Degnan, J. H.; Grabowski, C.; Ruden, E. L.

2003-10-01

Our research plans for FRX-L, the field reversed configuration plasma injector at LANL for magnetized target fusion (MTF), have been planned for the next 4-year period. FRX-L has been successfully operating now for the last two years, although construction for both the machine and diagnostic sets is ongoing. Efforts in FY04 begin with continued improvements in the basic high density FRC parameters, through operation at increased magnetic fields and with the addition of a more effective main bank crowbar to reduce parasitic ringing in the high current main coil circuit. Translation experiments into a "fake" metal liner, perforated with diagnostic access ports, will start after designing and constructing the translation section. Another bank of capacitors will be added to power the additional guide and mirror coils. After demonstrating trapping of the plasma in the aluminum liner, and diagnosing sufficient plasma parameters (density, temperature, lifetime, purity), we will begin preparations for the integrated plasma/liner compression experiment at the Air Force Research Laboratory Shiva-Star machine in FY05. Construction of the new hardware will continue during FY06, and the first fusion-relevant demonstration of compression of plasma by an imploding metal liner is planned for FY07. Our MTF plans also include new initiatives with U of Washington, U of Wisconsin, and the University of New Mexico, in addition to ongoing theory ties to LLNL and GA.

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.

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.

Data Distribution System (DDS) and Solar Dynamic Observatory Ground Station (SDOGS) Integration Manager

NASA Technical Reports Server (NTRS)

Pham, Kim; Bialas, Thomas

2012-01-01

The DDS SDOGS Integration Manager (DSIM) provides translation between native control and status formats for systems within DDS and SDOGS, and the ASIST (Advanced Spacecraft Integration and System Test) control environment in the SDO MOC (Solar Dynamics Observatory Mission Operations Center). This system was created in response for a need to centralize remote monitor and control of SDO Ground Station equipments using ASIST control environment in SDO MOC, and to have configurable table definition for equipment. It provides translation of status and monitoring information from the native systems into ASIST-readable format to display on pages in the MOC. The manager is lightweight, user friendly, and efficient. It allows data trending, correlation, and storing. It allows using ASIST as common interface for remote monitor and control of heterogeneous equipments. It also provides failover capability to back up machines.

Human anatomy nomenclature rules for the computer age.

PubMed

Neumann, Paul E; Baud, Robert; Sprumont, Pierre

2017-04-01

Information systems are increasing in importance in biomedical sciences and medical practice. The nomenclature rules of human anatomy were reviewed for adequacy with respect to modern needs. New rules are proposed here to ensure that each Latin term is uniquely associated with an anatomical entity, as short and simple as possible, and machine-interpretable. Observance of these recommendations will also benefit students and translators of the Latin terms into other languages. Clin. Anat. 30:300-302, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Integrated Systems of Automatic Radio Equipment,

DTIC Science & Technology

1982-05-20

Publishing House "Sovetskoye Radio", Moscow, 1968, pp. 1 -232 Country of origin: USSR This document is a machine translation. Requester: USAMICOM...5 Chapter 1 , Fundamental Characteristics of the Meters of Integrated Systems .. .................. ........... 12 Chapter 2...ts 3 3 3 7 Z, z 91 4 Ch, ch Ku I, i LU w s11 Sh, sh a 0 Y, y W . NJ Shch, shch X x K, k b It f A7 , L, 1 --- - - Y, y . MM M, m = I & . H H N, n 3 3

Neurofeedback Training for BCI Control

NASA Astrophysics Data System (ADS)

Neuper, Christa; Pfurtscheller, Gert

Brain-computer interface (BCI) systems detect changes in brain signals that reflect human intention, then translate these signals to control monitors or external devices (for a comprehensive review, see [1]). BCIs typically measure electrical signals resulting from neural firing (i.e. neuronal action potentials, Electroencephalogram (ECoG), or Electroencephalogram (EEG)). Sophisticated pattern recognition and classification algorithms convert neural activity into the required control signals. BCI research has focused heavily on developing powerful signal processing and machine learning techniques to accurately classify neural activity [2-4].

Computational Linguistics in Military Operations

DTIC Science & Technology

2010-01-01

information dominance at the operational and tactical level of war in future warfare. Discussion: Mastering culture and language in a foreign country is decisive to understand the operational environment. In addition, the ability to understand and speak a foreign language is a prerequisite to achieve truly comprehension of an unfamiliar culture. Lasting operations in Afghanistan and Iraq and the necessity to breach the language gap lead to progress in the field of Machine Translation and the development of technical solutions to close the gap in the past decade. This paper

Translations from Red Flag No. 9, 3 September 1978

DTIC Science & Technology

1978-11-06

of the Death of Great Leader and Teacher Chairman Mao (pp 18-23) (Hsu Shih -yu) • 23 Deeply Cherish the Memory of Comrade Lo Jui-ching, an...well. At the First National Conference on Learning From Tachai in Agriculture, Comrade Hua Kuo -feng called on all departments of the party Central^Com...in acting like "Chin Shih Huang." As to how to reorganize the farm machinery industry, however, the First Ministry of Machine Building should make

Genome-Wide Analysis of Translational Control in Tuberous Sclerosis Complex

DTIC Science & Technology

2012-07-01

particular non-AUG codons in the 5’UTR. However, these data was “noisy” and required a machine-learning algorithm to identify TIS codons. We develop...To investigate how nutrient signaling affects the folding of nascent chains, we used firefly luciferase (Luc) as a reporter because of its high...folding as the structural basis for the rapid de novo folding of firefly luciferase. Nat Struct Biol 6(7):697-705. 12. Gupta R, Kasturi P, Bracher A

NASA STI Program Coordinating Council Eleventh Meeting: NASA STI Modernization Plan

NASA Technical Reports Server (NTRS)

1993-01-01

The theme of this NASA Scientific and Technical Information Program Coordinating Council Meeting was the modernization of the STI Program. Topics covered included the activities of the Engineering Review Board in the creation of the Infrastructure Upgrade Plan, the progress of the RECON Replacement Project, the use and status of Electronic SCAN (Selected Current Aerospace Notices), the Machine Translation Project, multimedia, electronic document interchange, the NASA Access Mechanism, computer network upgrades, and standards in the architectural effort.

Balanced-Rotating-Spray Tank-And-Pipe-Cleaning System

NASA Technical Reports Server (NTRS)

Thaxton, Eric A.; Caimi, Raoul E. B.

1995-01-01

Spray head translates and rotates to clean entire inner surface of tank or pipe. Cleansing effected by three laterally balanced gas/liquid jets from spray head that rotates about longitudinal axis. Uses much less liquid. Cleaning process in system relies on mechanical action of jets instead of contaminant dissolution. Eliminates very difficult machining needed to make multiple converging/diverging nozzles within one spray head. Makes nozzle much smaller. Basic two-phase-flow, supersonic-nozzle design applied to other spray systems for interior or exterior cleaning.

Visualization of anthropometric measures of workers in computer 3D modeling of work place.

PubMed

Mijović, B; Ujević, D; Baksa, S

2001-12-01

In this work, 3D visualization of a work place by means of a computer-made 3D-machine model and computer animation of a worker have been performed. By visualization of 3D characters in inverse kinematic and dynamic relation with the operating part of a machine, the biomechanic characteristics of worker's body have been determined. The dimensions of a machine have been determined by an inspection of technical documentation as well as by direct measurements and recordings of the machine by camera. On the basis of measured body height of workers all relevant anthropometric measures have been determined by a computer program developed by the authors. By knowing the anthropometric measures, the vision fields and the scope zones while forming work places, exact postures of workers while performing technological procedures were determined. The minimal and maximal rotation angles and the translation of upper and lower arm which are basis for the analysis of worker burdening were analyzed. The dimensions of the seized space of a body are obtained by computer anthropometric analysis of movement, e.g. range of arms, position of legs, head, back. The influence of forming of a work place on correct postures of workers during work has been reconsidered and thus the consumption of energy and fatigue can be reduced to a minimum.

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

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.

The Oregon State University wind studies. [economic feasibility of windpowered generators

NASA Technical Reports Server (NTRS)

Wilson, R. E.

1973-01-01

The economic feasibility of commercial use of wind generated power in selected areas of Oregon is assessed. A number of machines for generating power have been examined. These include the Savonius rotor, translators, conventional wind turbines, the circulation controlled rotor and the vertical axis winged turbine. Of these machines, the conventional wind turbine and the vertical axis winged turbine show the greatest promise on the basis of the power developed per unit of rotor blade area. Attention has been focused on the structural and fatigue analysis of rotors since the economics of rotary winged, wind generated power depends upon low cost, long lifetime rotors. Analysis of energy storage systems and tower design has also been undertaken. An economic means of energy storage has not been found to date. Tower design studies have produced cost estimates that are in general agreement with the cost of the updated Putnam 110-foot tower.

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

Jones, J.P.; Bangs, A.L.; Butler, P.L.

Hetero Helix is a programming environment which simulates shared memory on a heterogeneous network of distributed-memory computers. The machines in the network may vary with respect to their native operating systems and internal representation of numbers. Hetero Helix presents a simple programming model to developers, and also considers the needs of designers, system integrators, and maintainers. The key software technology underlying Hetero Helix is the use of a compiler'' which analyzes the data structures in shared memory and automatically generates code which translates data representations from the format native to each machine into a common format, and vice versa. Themore » design of Hetero Helix was motivated in particular by the requirements of robotics applications. Hetero Helix has been used successfully in an integration effort involving 27 CPUs in a heterogeneous network and a body of software totaling roughly 100,00 lines of code. 25 refs., 6 figs.« less

Stability of a dragged viscous thread: Onset of ``stitching'' in a fluid-mechanical ``sewing machine''

NASA Astrophysics Data System (ADS)

Ribe, Neil M.; Lister, John R.; Chiu-Webster, Sunny

2006-12-01

A thin thread of viscous fluid that falls on a moving belt acts like a fluid-mechanical "sewing machine," exhibiting a rich variety of "stitch" patterns including meanders, translated coiling, slanted loops, braiding, figures-of-eight, W-patterns, side kicks, and period-doubled patterns. Using a numerical linear stability analysis, we determine the critical belt speed and oscillation frequency of the first bifurcation, at which a steady dragged viscous thread becomes unstable to transverse oscillations or "meandering." The predictions of the stability analysis agree closely with the experimental measurements of Chiu-Webster and Lister [J. Fluid Mech. 569, 89 (2006)]. Moreover, the critical belt speed and onset frequency for meandering are nearly identical to the contact-point migration speed and angular frequency, respectively, of steady coiling of a viscous thread on a stationary surface, implying a remarkable degree of dynamical similarity between the two phenomena.

Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure.

PubMed

Orlenko, Alena; Moore, Jason H; Orzechowski, Patryk; Olson, Randal S; Cairns, Junmei; Caraballo, Pedro J; Weinshilboum, Richard M; Wang, Liewei; Breitenstein, Matthew K

2018-01-01

With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide exciting opportunity to guide feature selection in agnostic metabolic profiling endeavors, where potentially thousands of independent data points must be evaluated. In previous research, AutoML using high-dimensional data of varying types has been demonstrably robust, outperforming traditional approaches. However, considerations for application in clinical metabolic profiling remain to be evaluated. Particularly, regarding the robustness of AutoML to identify and adjust for common clinical confounders. In this study, we present a focused case study regarding AutoML considerations for using the Tree-Based Optimization Tool (TPOT) in metabolic profiling of exposure to metformin in a biobank cohort. First, we propose a tandem rank-accuracy measure to guide agnostic feature selection and corresponding threshold determination in clinical metabolic profiling endeavors. Second, while AutoML, using default parameters, demonstrated potential to lack sensitivity to low-effect confounding clinical covariates, we demonstrated residual training and adjustment of metabolite features as an easily applicable approach to ensure AutoML adjustment for potential confounding characteristics. Finally, we present increased homocysteine with long-term exposure to metformin as a potentially novel, non-replicated metabolite association suggested by TPOT; an association not identified in parallel clinical metabolic profiling endeavors. While warranting independent replication, our tandem rank-accuracy measure suggests homocysteine to be the metabolite feature with largest effect, and corresponding priority for further translational clinical research. Residual training and adjustment for a potential confounding effect by BMI only slightly modified the suggested association. Increased homocysteine is thought to be associated with vitamin B12 deficiency - evaluation for potential clinical relevance is suggested. While considerations for clinical metabolic profiling are recommended, including adjustment approaches for clinical confounders, AutoML presents an exciting tool to enhance clinical metabolic profiling and advance translational research endeavors.

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.

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.

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 .

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.

Research in speech communication.

PubMed Central

Flanagan, J

1995-01-01

Advances in digital speech processing are now supporting application and deployment of a variety of speech technologies for human/machine communication. In fact, new businesses are rapidly forming about these technologies. But these capabilities are of little use unless society can afford them. Happily, explosive advances in microelectronics over the past two decades have assured affordable access to this sophistication as well as to the underlying computing technology. The research challenges in speech processing remain in the traditionally identified areas of recognition, synthesis, and coding. These three areas have typically been addressed individually, often with significant isolation among the efforts. But they are all facets of the same fundamental issue--how to represent and quantify the information in the speech signal. This implies deeper understanding of the physics of speech production, the constraints that the conventions of language impose, and the mechanism for information processing in the auditory system. In ongoing research, therefore, we seek more accurate models of speech generation, better computational formulations of language, and realistic perceptual guides for speech processing--along with ways to coalesce the fundamental issues of recognition, synthesis, and coding. Successful solution will yield the long-sought dictation machine, high-quality synthesis from text, and the ultimate in low bit-rate transmission of speech. It will also open the door to language-translating telephony, where the synthetic foreign translation can be in the voice of the originating talker. Images Fig. 1 Fig. 2 Fig. 5 Fig. 8 Fig. 11 Fig. 12 Fig. 13 PMID:7479806

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.

Automated 3D structure composition for large RNAs

PubMed Central

Popenda, Mariusz; Szachniuk, Marta; Antczak, Maciej; Purzycka, Katarzyna J.; Lukasiak, Piotr; Bartol, Natalia; Blazewicz, Jacek; Adamiak, Ryszard W.

2012-01-01

Understanding the numerous functions that RNAs play in living cells depends critically on knowledge of their three-dimensional structure. Due to the difficulties in experimentally assessing structures of large RNAs, there is currently great demand for new high-resolution structure prediction methods. We present the novel method for the fully automated prediction of RNA 3D structures from a user-defined secondary structure. The concept is founded on the machine translation system. The translation engine operates on the RNA FRABASE database tailored to the dictionary relating the RNA secondary structure and tertiary structure elements. The translation algorithm is very fast. Initial 3D structure is composed in a range of seconds on a single processor. The method assures the prediction of large RNA 3D structures of high quality. Our approach needs neither structural templates nor RNA sequence alignment, required for comparative methods. This enables the building of unresolved yet native and artificial RNA structures. The method is implemented in a publicly available, user-friendly server RNAComposer. It works in an interactive mode and a batch mode. The batch mode is designed for large-scale modelling and accepts atomic distance restraints. Presently, the server is set to build RNA structures of up to 500 residues. PMID:22539264

Classifying chemical mode of action using gene networks and machine learning: a case study with the herbicide linuron.

PubMed

Ornostay, Anna; Cowie, Andrew M; Hindle, Matthew; Baker, Christopher J O; Martyniuk, Christopher J

2013-12-01

The herbicide linuron (LIN) is an endocrine disruptor with an anti-androgenic mode of action. The objectives of this study were to (1) improve knowledge of androgen and anti-androgen signaling in the teleostean ovary and to (2) assess the ability of gene networks and machine learning to classify LIN as an anti-androgen using transcriptomic data. Ovarian explants from vitellogenic fathead minnows (FHMs) were exposed to three concentrations of either 5α-dihydrotestosterone (DHT), flutamide (FLUT), or LIN for 12h. Ovaries exposed to DHT showed a significant increase in 17β-estradiol (E2) production while FLUT and LIN had no effect on E2. To improve understanding of androgen receptor signaling in the ovary, a reciprocal gene expression network was constructed for DHT and FLUT using pathway analysis and these data suggested that steroid metabolism, translation, and DNA replication are processes regulated through AR signaling in the ovary. Sub-network enrichment analysis revealed that FLUT and LIN shared more regulated gene networks in common compared to DHT. Using transcriptomic datasets from different fish species, machine learning algorithms classified LIN successfully with other anti-androgens. This study advances knowledge regarding molecular signaling cascades in the ovary that are responsive to androgens and anti-androgens and provides proof of concept that gene network analysis and machine learning can classify priority chemicals using experimental transcriptomic data collected from different fish species. © 2013.

Hand-in-hand advances in biomedical engineering and sensorimotor restoration.

PubMed

Pisotta, Iolanda; Perruchoud, David; Ionta, Silvio

2015-05-15

Living in a multisensory world entails the continuous sensory processing of environmental information in order to enact appropriate motor routines. The interaction between our body and our brain is the crucial factor for achieving such sensorimotor integration ability. Several clinical conditions dramatically affect the constant body-brain exchange, but the latest developments in biomedical engineering provide promising solutions for overcoming this communication breakdown. The ultimate technological developments succeeded in transforming neuronal electrical activity into computational input for robotic devices, giving birth to the era of the so-called brain-machine interfaces. Combining rehabilitation robotics and experimental neuroscience the rise of brain-machine interfaces into clinical protocols provided the technological solution for bypassing the neural disconnection and restore sensorimotor function. Based on these advances, the recovery of sensorimotor functionality is progressively becoming a concrete reality. However, despite the success of several recent techniques, some open issues still need to be addressed. Typical interventions for sensorimotor deficits include pharmaceutical treatments and manual/robotic assistance in passive movements. These procedures achieve symptoms relief but their applicability to more severe disconnection pathologies is limited (e.g. spinal cord injury or amputation). Here we review how state-of-the-art solutions in biomedical engineering are continuously increasing expectances in sensorimotor rehabilitation, as well as the current challenges especially with regards to the translation of the signals from brain-machine interfaces into sensory feedback and the incorporation of brain-machine interfaces into daily activities. Copyright © 2015 Elsevier B.V. All rights reserved.

Climate and Man (Selected Articles),

DTIC Science & Technology

1985-08-09

6). Large Caucasus. (7). True altitude, m. a - Alibek; b - Sheki; c - Zakataly; d - Yevlakh; e - Kirovabad; f - Zurnabad; g -Shusha; h - Kedabek...b 10 8 a Ff. M., C m np Ro s a E. 11., q aa 1 4 . r7. 0nmTr pexpea- umwuoueILHKII TeppHT~pHHf MOCKoRCKolk oOAaCTH Ro *pH3HoAoro- KAH marH te - CKNM...MACHINE TRANSLATION FTD-ID(RS)T-1542-84 9 August 1985 MICROFICHE NR: FTD-85- C -Ooo647 CLIMATE AND MAN (Selected Articles) English pages: 171 Source: Klimat

Introduction to China’s Aeronautical Engineering Institutions of Higher Learning -- Student Enrollment in 1981 in Higher Aeronautical Colleges and Schools Administered by the Third Ministry of Machine Building

DTIC Science & Technology

1981-10-13

FTD-ID(RS )T-1029-81 Si FOREIGN TECHNOLOGY DIVISION INTRODUCTION TO CHINA’S AERONAUTICAL ENGINEERING INSTITUTIONS OF HIGHER LEARNING -- STUDENT...TRODUCTION TO JWINA’ S PRONAUTICAL ,NGINEERING 7’ S- NSTITUTIONS OF •IGHER LEARNING -- 4TUDENT I-ENROLLMENT IN 1951 IN ITGHER AERONAUTICAL OLLEGES AND...BYs ADVOCATEDOR IMPLIED ARE THOSE Ot THE SOURCE AND DO NOT NECESSARILY REFLECT THE POSITION TRANSLATION DIVISION OR OPINION OF THE FOREIGN TECHNOLOGY

APT - NASA ENHANCED VERSION OF AUTOMATICALLY PROGRAMMED TOOL SOFTWARE - STAND-ALONE VERSION

NASA Technical Reports Server (NTRS)

Premo, D. A.

1994-01-01

The APT code is one of the most widely used software tools for complex numerically controlled (N/C) machining. APT is an acronym for Automatically Programmed Tools and is used to denote both a language and the computer software that processes that language. Development of the APT language and software system was begun over twenty years ago as a U. S. government sponsored industry and university research effort. APT is a "problem oriented" language that was developed for the explicit purpose of aiding the N/C machine tools. Machine-tool instructions and geometry definitions are written in the APT language to constitute a "part program." The APT part program is processed by the APT software to produce a cutter location (CL) file. This CL file may then be processed by user supplied post processors to convert the CL data into a form suitable for a particular N/C machine tool. This June, 1989 offering of the APT system represents an adaptation, with enhancements, of the public domain version of APT IV/SSX8 to the DEC VAX-11/780 for use by the Engineering Services Division of the NASA Goddard Space Flight Center. Enhancements include the super pocket feature which allows concave and convex polygon shapes of up to 40 points including shapes that overlap, that leave islands of material within the pocket, and that have one or more arcs as part of the pocket boundary. Recent modifications to APT include a rework of the POCKET subroutine and correction of an error that prevented the use within a macro of a macro variable cutter move statement combined with macro variable double check surfaces. Former modifications included the expansion of array and buffer sizes to accommodate larger part programs, and the insertion of a few user friendly error messages. The APT system software on the DEC VAX-11/780 is organized into two separate programs: the load complex and the APT processor. The load complex handles the table initiation phase and is usually only run when changes to the APT processor capabilities are made. This phase initializes character recognition and syntax tables for the APT processor by creating FORTRAN block data programs. The APT processor consists of four components: the translator, the execution complex, the subroutine library, and the CL editor. The translator examines each APT statement in the part program for recognizable structure and generates a new statement, or series of statements, in an intermediate language. The execution complex processes all of the definition, motion, and related statements to generate cutter location coordinates. The subroutine library contains routines defining the algorithms required to process the sequenced list of intermediate language commands generated by the translator. The CL editor re-processes the cutter location coordinates according to user supplied commands to generate a final CL file. A sample post processor is also included which translates a CL file into a form for use with a Wales Strippit Fabramatic Model 30/30 sheet metal punch. The user should be able to readily develop post processors for other N/C machine tools. The APT language is a statement oriented, sequence dependent language. With the exception of such programming techniques as looping and macros, statements in an APT program are executed in a strict first-to-last sequence. In order to provide programming capability for the broadest possible range of parts and of machine tools, APT input (and output) is generalized, as represented by 3-dimensional geometry and tools, and arbitrarily uniform, as represented by the moving tool concept and output data in absolute coordinates. A command procedure allows the user to select the desired part program, ask for a graphics file of cutter motions in IGES format, and submit the procedure as a batch job, if desired. The APT system software is written in FORTRAN 77 for batch and interactive execution and has been implemented on a DEC VAX series computer under VMS 4.4. The enhancements for this version of APT were last updated in June, 1989. The NASA adaptation, with enhancements, of the public domain version of the APT IV/SSX8 software to the DEC VAX-11/780 is available by license for a period of ten (10) years to approved licensees. The licensed program product delivered includes the APT IV/SSX8 system source code, object code, executable images, and command procedures and one set of supporting documentation. Additional copies of the supporting documentation may be purchased at any time at the price indicated below.

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.

AnatomicalTerms.info: heading for an online solution to the anatomical synonym problem hurdles in data-reuse from the Terminologia Anatomica and the foundational model of anatomy and potentials for future development.

PubMed

Gobée, O Paul; Jansma, Daniël; DeRuiter, Marco C

2011-10-01

The many synonyms for anatomical structures confuse medical students and complicate medical communication. Easily accessible translations would alleviate this problem. None of the presently available resources-Terminologia Anatomica (TA), digital terminologies such as the Foundational Model of Anatomy (FMA), and websites-are fully satisfactory to this aim. Internet technologies offer new possibilities to solve the problem. Several authors have called for an online TA. An online translation resource should be easily accessible, user-friendly, comprehensive, expandable, and its quality determinable. As first step towards this goal, we built a translation website that we named www.AnatomicalTerms.info, based on the database of the FMA. It translates between English, Latin, eponyms, and to a lesser extent other languages, and presently contains over 31,000 terms for 7,250 structures, covering 95% of TA. In addition, it automatically presents searches for images, documents and anatomical variations regarding the sought structure. Several terminological and conceptual issues were encountered in transferring data from TA and FMA into AnatomicalTerms.info, resultant from these resources' different set-ups (paper versus digital) and targets (machine versus human-user). To the best of our knowledge, AnatomicalTerms.info is unique in its combination of user-friendliness and comprehensiveness. As next step, wiki-like expandability will be added to enable open contribution of clinical synonyms and terms in different languages. Specific quality measures will be taken to strike a balance between open contribution and quality assurance. AnatomicalTerms.info's mechanism that "translates" terms to structures furthermore may enhance targeted searching by linking images, descriptions, and other anatomical resources to the structures. Copyright © 2011 Wiley-Liss, Inc.

KARL: A Knowledge-Assisted Retrieval Language. M.S. Thesis Final Report, 1 Jul. 1985 - 31 Dec. 1987

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Triantafyllopoulos, Spiros

1985-01-01

Data classification and storage are tasks typically performed by application specialists. In contrast, information users are primarily non-computer specialists who use information in their decision-making and other activities. Interaction efficiency between such users and the computer is often reduced by machine requirements and resulting user reluctance to use the system. This thesis examines the problems associated with information retrieval for non-computer specialist users, and proposes a method for communicating in restricted English that uses knowledge of the entities involved, relationships between entities, and basic English language syntax and semantics to translate the user requests into formal queries. The proposed method includes an intelligent dictionary, syntax and semantic verifiers, and a formal query generator. In addition, the proposed system has a learning capability that can improve portability and performance. With the increasing demand for efficient human-machine communication, the significance of this thesis becomes apparent. As human resources become more valuable, software systems that will assist in improving the human-machine interface will be needed and research addressing new solutions will be of utmost importance. This thesis presents an initial design and implementation as a foundation for further research and development into the emerging field of natural language database query systems.

Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties

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

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

We introduce a fingerprint representation of molecules based on a Fourier series of atomic radial distribution functions. This fingerprint is unique (except for chirality), continuous, and differentiable with respect to atomic coordinates and nuclear charges. It is invariant with respect to translation, rotation, and nuclear permutation, and requires no preconceived knowledge about chemical bonding, topology, or electronic orbitals. As such, it meets many important criteria for a good molecular representation, suggesting its usefulness for machine learning models of molecular properties trained across chemical compound space. To assess the performance of this new descriptor, we have trained machine learning models ofmore » molecular enthalpies of atomization for training sets with up to 10 k organic molecules, drawn at random from a published set of 134 k organic molecules with an average atomization enthalpy of over 1770 kcal/mol. We validate the descriptor on all remaining molecules of the 134 k set. For a training set of 10 k molecules, the fingerprint descriptor achieves a mean absolute error of 8.0 kcal/mol. This is slightly worse than the performance attained using the Coulomb matrix, another popular alternative, reaching 6.2 kcal/mol for the same training and test sets. (c) 2015 Wiley Periodicals, Inc.« less

Design and validation of a real-time spiking-neural-network decoder for brain-machine interfaces

NASA Astrophysics Data System (ADS)

Dethier, Julie; Nuyujukian, Paul; Ryu, Stephen I.; Shenoy, Krishna V.; Boahen, Kwabena

2013-06-01

Objective. 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. Approach. 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). Main results. 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. Significance. 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.

Stable hovering of a jellyfish-like flying machine

PubMed Central

Ristroph, Leif; Childress, Stephen

2014-01-01

Ornithopters, or flapping-wing aircraft, offer an alternative to helicopters in achieving manoeuvrability at small scales, although stabilizing such aerial vehicles remains a key challenge. Here, we present a hovering machine that achieves self-righting flight using flapping wings alone, without relying on additional aerodynamic surfaces and without feedback control. We design, construct and test-fly a prototype that opens and closes four wings, resembling the motions of swimming jellyfish more so than any insect or bird. Measurements of lift show the benefits of wing flexing and the importance of selecting a wing size appropriate to the motor. Furthermore, we use high-speed video and motion tracking to show that the body orientation is stable during ascending, forward and hovering flight modes. Our experimental measurements are used to inform an aerodynamic model of stability that reveals the importance of centre-of-mass location and the coupling of body translation and rotation. These results show the promise of flapping-flight strategies beyond those that directly mimic the wing motions of flying animals. PMID:24430122

Exploring Deep Learning and Sparse Matrix Format Selection

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

Zhao, Y.; Liao, C.; Shen, X.

We proposed to explore the use of Deep Neural Networks (DNN) for addressing the longstanding barriers. The recent rapid progress of DNN technology has created a large impact in many fields, which has significantly improved the prediction accuracy over traditional machine learning techniques in image classifications, speech recognitions, machine translations, and so on. To some degree, these tasks resemble the decision makings in many HPC tasks, including the aforementioned format selection for SpMV and linear solver selection. For instance, sparse matrix format selection is akin to image classification—such as, to tell whether an image contains a dog or a cat;more » in both problems, the right decisions are primarily determined by the spatial patterns of the elements in an input. For image classification, the patterns are of pixels, and for sparse matrix format selection, they are of non-zero elements. DNN could be naturally applied if we regard a sparse matrix as an image and the format selection or solver selection as classification problems.« less

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.

Learning disordered topological phases by statistical recovery of symmetry

NASA Astrophysics Data System (ADS)

Yoshioka, Nobuyuki; Akagi, Yutaka; Katsura, Hosho

2018-05-01

We apply the artificial neural network in a supervised manner to map out the quantum phase diagram of disordered topological superconductors in class DIII. Given the disorder that keeps the discrete symmetries of the ensemble as a whole, translational symmetry which is broken in the quasiparticle distribution individually is recovered statistically by taking an ensemble average. By using this, we classify the phases by the artificial neural network that learned the quasiparticle distribution in the clean limit and show that the result is totally consistent with the calculation by the transfer matrix method or noncommutative geometry approach. If all three phases, namely the Z2, trivial, and thermal metal phases, appear in the clean limit, the machine can classify them with high confidence over the entire phase diagram. If only the former two phases are present, we find that the machine remains confused in a certain region, leading us to conclude the detection of the unknown phase which is eventually identified as the thermal metal phase.

Development of a HIPAA-compliant environment for translational research data and analytics.

PubMed

Bradford, Wayne; Hurdle, John F; LaSalle, Bernie; Facelli, Julio C

2014-01-01

High-performance computing centers (HPC) traditionally have far less restrictive privacy management policies than those encountered in healthcare. We show how an HPC can be re-engineered to accommodate clinical data while retaining its utility in computationally intensive tasks such as data mining, machine learning, and statistics. We also discuss deploying protected virtual machines. A critical planning step was to engage the university's information security operations and the information security and privacy office. Access to the environment requires a double authentication mechanism. The first level of authentication requires access to the university's virtual private network and the second requires that the users be listed in the HPC network information service directory. The physical hardware resides in a data center with controlled room access. All employees of the HPC and its users take the university's local Health Insurance Portability and Accountability Act training series. In the first 3 years, researcher count has increased from 6 to 58.

New Web Server - the Java Version of Tempest - Produced

NASA Technical Reports Server (NTRS)

York, David W.; Ponyik, Joseph G.

2000-01-01

A new software design and development effort has produced a Java (Sun Microsystems, Inc.) version of the award-winning Tempest software (refs. 1 and 2). In 1999, the Embedded Web Technology (EWT) team received a prestigious R&D 100 Award for Tempest, Java Version. In this article, "Tempest" will refer to the Java version of Tempest, a World Wide Web server for desktop or embedded systems. Tempest was designed at the NASA Glenn Research Center at Lewis Field to run on any platform for which a Java Virtual Machine (JVM, Sun Microsystems, Inc.) exists. The JVM acts as a translator between the native code of the platform and the byte code of Tempest, which is compiled in Java. These byte code files are Java executables with a ".class" extension. Multiple byte code files can be zipped together as a "*.jar" file for more efficient transmission over the Internet. Today's popular browsers, such as Netscape (Netscape Communications Corporation) and Internet Explorer (Microsoft Corporation) have built-in Virtual Machines to display Java applets.

A Cross-Lingual Similarity Measure for Detecting Biomedical Term Translations

PubMed Central

Bollegala, Danushka; Kontonatsios, Georgios; Ananiadou, Sophia

2015-01-01

Bilingual dictionaries for technical terms such as biomedical terms are an important resource for machine translation systems as well as for humans who would like to understand a concept described in a foreign language. Often a biomedical term is first proposed in English and later it is manually translated to other languages. Despite the fact that there are large monolingual lexicons of biomedical terms, only a fraction of those term lexicons are translated to other languages. Manually compiling large-scale bilingual dictionaries for technical domains is a challenging task because it is difficult to find a sufficiently large number of bilingual experts. We propose a cross-lingual similarity measure for detecting most similar translation candidates for a biomedical term specified in one language (source) from another language (target). Specifically, a biomedical term in a language is represented using two types of features: (a) intrinsic features that consist of character n-grams extracted from the term under consideration, and (b) extrinsic features that consist of unigrams and bigrams extracted from the contextual windows surrounding the term under consideration. We propose a cross-lingual similarity measure using each of those feature types. First, to reduce the dimensionality of the feature space in each language, we propose prototype vector projection (PVP)—a non-negative lower-dimensional vector projection method. Second, we propose a method to learn a mapping between the feature spaces in the source and target language using partial least squares regression (PLSR). The proposed method requires only a small number of training instances to learn a cross-lingual similarity measure. The proposed PVP method outperforms popular dimensionality reduction methods such as the singular value decomposition (SVD) and non-negative matrix factorization (NMF) in a nearest neighbor prediction task. Moreover, our experimental results covering several language pairs such as English–French, English–Spanish, English–Greek, and English–Japanese show that the proposed method outperforms several other feature projection methods in biomedical term translation prediction tasks. PMID:26030738

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.

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.

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 2: From Clinical Implementation to Enterprise.

PubMed

Shaikh, Faiq; Franc, Benjamin; Allen, Erastus; Sala, Evis; Awan, Omer; Hendrata, Kenneth; Halabi, Safwan; Mohiuddin, Sohaib; Malik, Sana; Hadley, Dexter; Shrestha, Rasu

2018-03-01

Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. More recently, the advancement in the field of quantitative image analysis coupled with machine learning-based data analytics, classification, and integration has ushered in the era of radiomics, a paradigm shift that holds tremendous potential in clinical decision support as well as drug discovery. However, there are important issues to consider to incorporate radiomics into a clinically applicable system and a commercially viable solution. In this two-part series, we offer insights into the development of the translational pipeline for radiomics from methodology to clinical implementation (Part 1) and from that point to enterprise development (Part 2). In Part 2 of this two-part series, we study the components of the strategy pipeline, from clinical implementation to building enterprise solutions. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Combat Wound Initiative program.

PubMed

Stojadinovic, Alexander; Elster, Eric; Potter, Benjamin K; Davis, Thomas A; Tadaki, Doug K; Brown, Trevor S; Ahlers, Stephen; Attinger, Christopher E; Andersen, Romney C; Burris, David; Centeno, Jose; Champion, Hunter; Crumbley, David R; Denobile, John; Duga, Michael; Dunne, James R; Eberhardt, John; Ennis, William J; Forsberg, Jonathan A; Hawksworth, Jason; Helling, Thomas S; Lazarus, Gerald S; Milner, Stephen M; Mullick, Florabel G; Owner, Christopher R; Pasquina, Paul F; Patel, Chirag R; Peoples, George E; Nissan, Aviram; Ring, Michael; Sandberg, Glenn D; Schaden, Wolfgang; Schultz, Gregory S; Scofield, Tom; Shawen, Scott B; Sheppard, Forest R; Stannard, James P; Weina, Peter J; Zenilman, Jonathan M

2010-07-01

The Combat Wound Initiative (CWI) program is a collaborative, multidisciplinary, and interservice public-private partnership that provides personalized, state-of-the-art, and complex wound care via targeted clinical and translational research. The CWI uses a bench-to-bedside approach to translational research, including the rapid development of a human extracorporeal shock wave therapy (ESWT) study in complex wounds after establishing the potential efficacy, biologic mechanisms, and safety of this treatment modality in a murine model. Additional clinical trials include the prospective use of clinical data, serum and wound biomarkers, and wound gene expression profiles to predict wound healing/failure and additional clinical patient outcomes following combat-related trauma. These clinical research data are analyzed using machine-based learning algorithms to develop predictive treatment models to guide clinical decision-making. Future CWI directions include additional clinical trials and study centers and the refinement and deployment of our genetically driven, personalized medicine initiative to provide patient-specific care across multiple medical disciplines, with an emphasis on combat casualty care.

A Systematic Comparison of Data Selection Criteria for SMT Domain Adaptation

PubMed Central

Chao, Lidia S.; Lu, Yi; Xing, Junwen

2014-01-01

Data selection has shown significant improvements in effective use of training data by extracting sentences from large general-domain corpora to adapt statistical machine translation (SMT) systems to in-domain data. This paper performs an in-depth analysis of three different sentence selection techniques. The first one is cosine tf-idf, which comes from the realm of information retrieval (IR). The second is perplexity-based approach, which can be found in the field of language modeling. These two data selection techniques applied to SMT have been already presented in the literature. However, edit distance for this task is proposed in this paper for the first time. After investigating the individual model, a combination of all three techniques is proposed at both corpus level and model level. Comparative experiments are conducted on Hong Kong law Chinese-English corpus and the results indicate the following: (i) the constraint degree of similarity measuring is not monotonically related to domain-specific translation quality; (ii) the individual selection models fail to perform effectively and robustly; but (iii) bilingual resources and combination methods are helpful to balance out-of-vocabulary (OOV) and irrelevant data; (iv) finally, our method achieves the goal to consistently boost the overall translation performance that can ensure optimal quality of a real-life SMT system. PMID:24683356

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.

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 machine learning approach for predicting methionine oxidation sites.

PubMed

Aledo, Juan C; Cantón, Francisco R; Veredas, Francisco J

2017-09-29

The oxidation of protein-bound methionine to form methionine sulfoxide, has traditionally been regarded as an oxidative damage. However, recent evidences support the view of this reversible reaction as a regulatory post-translational modification. The perception that methionine sulfoxidation may provide a mechanism to the redox regulation of a wide range of cellular processes, has stimulated some proteomic studies. However, these experimental approaches are expensive and time-consuming. Therefore, computational methods designed to predict methionine oxidation sites are an attractive alternative. As a first approach to this matter, we have developed models based on random forests, support vector machines and neural networks, aimed at accurate prediction of sites of methionine oxidation. Starting from published proteomic data regarding oxidized methionines, we created a hand-curated dataset formed by 113 unique polypeptides of known structure, containing 975 methionyl residues, 122 of which were oxidation-prone (positive dataset) and 853 were oxidation-resistant (negative dataset). We use a machine learning approach to generate predictive models from these datasets. Among the multiple features used in the classification task, some of them contributed substantially to the performance of the predictive models. Thus, (i) the solvent accessible area of the methionine residue, (ii) the number of residues between the analyzed methionine and the next methionine found towards the N-terminus and (iii) the spatial distance between the atom of sulfur from the analyzed methionine and the closest aromatic residue, were among the most relevant features. Compared to the other classifiers we also evaluated, random forests provided the best performance, with accuracy, sensitivity and specificity of 0.7468±0.0567, 0.6817±0.0982 and 0.7557±0.0721, respectively (mean ± standard deviation). We present the first predictive models aimed to computationally detect methionine sites that may become oxidized in vivo in response to oxidative signals. These models provide insights into the structural context in which a methionine residue become either oxidation-resistant or oxidation-prone. Furthermore, these models should be useful in prioritizing methinonyl residues for further studies to determine their potential as regulatory post-translational modification sites.

Identifying a clinical signature of suicidality among patients with mood disorders: A pilot study using a machine learning approach.

PubMed

Passos, Ives Cavalcante; Mwangi, Benson; Cao, Bo; Hamilton, Jane E; Wu, Mon-Ju; Zhang, Xiang Yang; Zunta-Soares, Giovana B; Quevedo, Joao; Kauer-Sant'Anna, Marcia; Kapczinski, Flávio; Soares, Jair C

2016-03-15

A growing body of evidence has put forward clinical risk factors associated with patients with mood disorders that attempt suicide. However, what is not known is how to integrate clinical variables into a clinically useful tool in order to estimate the probability of an individual patient attempting suicide. A total of 144 patients with mood disorders were included. Clinical variables associated with suicide attempts among patients with mood disorders and demographic variables were used to 'train' a machine learning algorithm. The resulting algorithm was utilized in identifying novel or 'unseen' individual subjects as either suicide attempters or non-attempters. Three machine learning algorithms were implemented and evaluated. All algorithms distinguished individual suicide attempters from non-attempters with prediction accuracy ranging between 65% and 72% (p<0.05). In particular, the relevance vector machine (RVM) algorithm correctly predicted 103 out of 144 subjects translating into 72% accuracy (72.1% sensitivity and 71.3% specificity) and an area under the curve of 0.77 (p<0.0001). The most relevant predictor variables in distinguishing attempters from non-attempters included previous hospitalizations for depression, a history of psychosis, cocaine dependence and post-traumatic stress disorder (PTSD) comorbidity. Risk for suicide attempt among patients with mood disorders can be estimated at an individual subject level by incorporating both demographic and clinical variables. Future studies should examine the performance of this model in other populations and its subsequent utility in facilitating selection of interventions to prevent suicide. Copyright © 2015 Elsevier B.V. All rights reserved.

Identifying a clinical signature of suicidality among patients with mood disorders: a pilot study using a machine learning approach

PubMed Central

Passos, Ives Cavalcante; Mwangi, Benson; Cao, Bo; Hamilton, Jane E; Wu, Mon-Ju; Zhang, Xiang Yang; Zunta-Soares, Giovana B.; Quevedo, Joao; Kauer-Sant'Anna, Marcia; Kapczinski, Flávio; Soares, Jair C.

2016-01-01

Objective A growing body of evidence has put forward clinical risk factors associated with patients with mood disorders that attempt suicide. However, what is not known is how to integrate clinical variables into a clinically useful tool in order to estimate the probability of an individual patient attempting suicide. Method A total of 144 patients with mood disorders were included. Clinical variables associated with suicide attempts among patients with mood disorders and demographic variables were used to ‘train’ a machine learning algorithm. The resulting algorithm was utilized in identifying novel or ‘unseen’ individual subjects as either suicide attempters or non-attempters. Three machine learning algorithms were implemented and evaluated. Results All algorithms distinguished individual suicide attempters from non-attempters with prediction accuracy ranging between 65%-72% (p<0.05). In particular, the relevance vector machine (RVM) algorithm correctly predicted 103 out of 144 subjects translating into 72% accuracy (72.1% sensitivity and 71.3% specificity) and an area under the curve of 0.77 (p<0.0001). The most relevant predictor variables in distinguishing attempters from non-attempters included previous hospitalizations for depression, a history of psychosis, cocaine dependence and post-traumatic stress disorder (PTSD) comorbidity. Conclusion Risk for suicide attempt among patients with mood disorders can be estimated at an individual subject level by incorporating both demographic and clinical variables. Future studies should examine the performance of this model in other populations and its subsequent utility in facilitating selection of interventions to prevent suicide. PMID:26773901

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.

Direct Production of 99mTc via 100Mo(p,2n) on Small Medical Cyclotrons

NASA Astrophysics Data System (ADS)

Schaffer, P.; Bénard, F.; Bernstein, A.; Buckley, K.; Celler, A.; Cockburn, N.; Corsaut, J.; Dodd, M.; Economou, C.; Eriksson, T.; Frontera, M.; Hanemaayer, V.; Hook, B.; Klug, J.; Kovacs, M.; Prato, F. S.; McDiarmid, S.; Ruth, T. J.; Shanks, C.; Valliant, J. F.; Zeisler, S.; Zetterberg, U.; Zavodszky, P. A.

From the efforts of a number of Canadian institutions and private industry collaborations, direct production of 99mTc using medical cyclotrons has recently been advanced from a 1970's academic exercise to a commercial, economically viable solution for regional production. Using GE PETtrace 880 machines our team has established preliminary saturated yields of 2.7 GBq/μA, translating to approximately 174 GBq after a 6 hour irradiation. The team is in the process of assessing the accuracy and reliability of this production value with a goal of optimizing yields by up to 50%.

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.

Single Molecule Force Measurement for Protein Synthesis on the Ribosome

NASA Astrophysics Data System (ADS)

Uemura, Sotaro

2008-04-01

The ribosome is a molecular machine that translates the genetic code described on the messenger RNA (mRNA) into an amino acid sequence through repetitive cycles of transfer RNA (tRNA) selection, peptide bond formation and translocation. Although the detailed interactions between the translation components have been revealed by extensive structural and biochemical studies, it is not known how the precise regulation of macromolecular movements required at each stage of translation is achieved. Here we demonstrate an optical tweezer assay to measure the rupture force between a single ribosome complex and mRNA. The rupture force was compared between ribosome complexes assembled on an mRNA with and without a strong Shine-Dalgarno (SD) sequence. The removal of the SD sequence significantly reduced the rupture force, indicating that the SD interactions contribute significantly to the stability of the ribosomal complex on the mRNA in a pre-peptidyl transfer state. In contrast, the post-peptidyl transfer state weakened the rupture force as compared to the complex in a pre-peptidyl transfer state and it was the same for both the SD-containing and SD-deficient mRNAs. The results suggest that formation of the first peptide bond destabilizes the SD interaction, resulting in the weakening of the force with which the ribosome grips an mRNA. This might be an important requirement to facilitate movement of the ribosome along mRNA during the first translocation step. In this article, we discuss about the above new results including the introduction of the ribosome translation mechanism and the optical tweezer method.

Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning.

PubMed

Zhao, Jonathan Z L; Mucaki, Eliseos J; Rogan, Peter K

2018-01-01

Background: Gene signatures derived from transcriptomic data using machine learning methods have shown promise for biodosimetry testing. These signatures may not be sufficiently robust for large scale testing, as their performance has not been adequately validated on external, independent datasets. The present study develops human and murine signatures with biochemically-inspired machine learning that are strictly validated using k-fold and traditional approaches. Methods: Gene Expression Omnibus (GEO) datasets of exposed human and murine lymphocytes were preprocessed via nearest neighbor imputation and expression of genes implicated in the literature to be responsive to radiation exposure (n=998) were then ranked by Minimum Redundancy Maximum Relevance (mRMR). Optimal signatures were derived by backward, complete, and forward sequential feature selection using Support Vector Machines (SVM), and validated using k-fold or traditional validation on independent datasets. Results: The best human signatures we derived exhibit k-fold validation accuracies of up to 98% ( DDB2 ,  PRKDC , TPP2 , PTPRE , and GADD45A ) when validated over 209 samples and traditional validation accuracies of up to 92% ( DDB2 ,  CD8A ,  TALDO1 ,  PCNA ,  EIF4G2 ,  LCN2 ,  CDKN1A ,  PRKCH ,  ENO1 ,  and PPM1D ) when validated over 85 samples. Some human signatures are specific enough to differentiate between chemotherapy and radiotherapy. Certain multi-class murine signatures have sufficient granularity in dose estimation to inform eligibility for cytokine therapy (assuming these signatures could be translated to humans). We compiled a list of the most frequently appearing genes in the top 20 human and mouse signatures. More frequently appearing genes among an ensemble of signatures may indicate greater impact of these genes on the performance of individual signatures. Several genes in the signatures we derived are present in previously proposed signatures. Conclusions: Gene signatures for ionizing radiation exposure derived by machine learning have low error rates in externally validated, independent datasets, and exhibit high specificity and granularity for dose estimation.

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.

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.

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.

Neurocognitive pattern analysis reveals classificatory hierarchy of attention deficits in schizophrenia.

PubMed

Shen, Christina; Popescu, Florin C; Hahn, Eric; Ta, Tam T M; Dettling, Michael; Neuhaus, Andres H

2014-07-01

Attention deficits, among other cognitive deficits, are frequently observed in schizophrenia. Although valid and reliable neurocognitive tasks have been established to assess attention deficits in schizophrenia, the hierarchical value of those tests as diagnostic discriminants on a single-subject level remains unclear. Thus, much research is devoted to attention deficits that are unlikely to be translated into clinical practice. On the other hand, a clear hierarchy of attention deficits in schizophrenia could considerably aid diagnostic decisions and may prove beneficial for longitudinal monitoring of therapeutic advances. To propose a diagnostic hierarchy of attention deficits in schizophrenia, we investigated several facets of attention in 86 schizophrenia patients and 86 healthy controls using a set of established attention tests. We applied state-of-the-art machine learning algorithms to determine attentive test variables that enable an automated differentiation between schizophrenia patients and healthy controls. After feature preranking, hypothesis building, and hypothesis validation, the polynomial support vector machine classifier achieved a classification accuracy of 90.70% ± 2.9% using psychomotor speed and 3 different attention parameters derived from sustained and divided attention tasks. Our study proposes, to the best of our knowledge, the first hierarchy of attention deficits in schizophrenia by identifying the most discriminative attention parameters among a variety of attention deficits found in schizophrenia patients. Our results offer a starting point for hierarchy building of schizophrenia-associated attention deficits and contribute to translating these concepts into diagnostic and therapeutic practice on a single-subject level. © The Author 2013. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Motor imaginary-based brain-machine interface design using programmable logic controllers for the disabled.

PubMed

Jeyabalan, Vickneswaran; Samraj, Andrews; Loo, Chu Kiong

2010-10-01

Aiming at the implementation of brain-machine interfaces (BMI) for the aid of disabled people, this paper presents a system design for real-time communication between the BMI and programmable logic controllers (PLCs) to control an electrical actuator that could be used in devices to help the disabled. Motor imaginary signals extracted from the brain’s motor cortex using an electroencephalogram (EEG) were used as a control signal. The EEG signals were pre-processed by means of adaptive recursive band-pass filtrations (ARBF) and classified using simplified fuzzy adaptive resonance theory mapping (ARTMAP) in which the classified signals are then translated into control signals used for machine control via the PLC. A real-time test system was designed using MATLAB for signal processing, KEP-Ware V4 OLE for process control (OPC), a wireless local area network router, an Omron Sysmac CPM1 PLC and a 5 V/0.3A motor. This paper explains the signal processing techniques, the PLC's hardware configuration, OPC configuration and real-time data exchange between MATLAB and PLC using the MATLAB OPC toolbox. The test results indicate that the function of exchanging real-time data can be attained between the BMI and PLC through OPC server and proves that it is an effective and feasible method to be applied to devices such as wheelchairs or electronic equipment.

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.

Modifications of Ti-6Al-4V surfaces by direct-write laser machining of linear grooves

NASA Astrophysics Data System (ADS)

Ulerich, Joseph P.; Ionescu, Lara C.; Chen, Jianbo; Soboyejo, Winston O.; Arnold, Craig B.

2007-02-01

As patients who receive orthopedic implants live longer and opt for surgery at a younger age, the need to extend the in vivo lifetimes of these implants has grown. One approach is to pattern implant surfaces with linear grooves, which elicit a cellular response known as contact guidance. Lasers provide a unique method of generating these surface patterns because they are capable of modifying physical and chemical properties over multiple length scales. In this paper we explore the relationship between surface morphology and laser parameters such as fluence, pulse overlap (translation distance), number of passes, and machining environment. We find that using simple procedures involving multiple passes it is possible to manipulate groove properties such as depth, shape, sub-micron roughness, and chemical composition of the Ti-6Al-4V oxide layer. Finally, we demonstrate this procedure by machining several sets of grooves with the same primary groove parameters but varied secondary characteristics. The significance of the secondary groove characteristics is demonstrated by preliminary cell studies indicating that the grooves exhibit basic features of contact guidance and that the cell proliferation in these grooves are significantly altered despite their similar primary characteristics. With further study it will be possible to use specific laser parameters during groove formation to create optimal physical and chemical properties for improved osseointegration.

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.

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.

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.

State but not district nutrition policies are associated with less junk food in vending machines and school stores in US public schools.

PubMed

Kubik, Martha Y; Wall, Melanie; Shen, Lijuan; Nanney, Marilyn S; Nelson, Toben F; Laska, Melissa N; Story, Mary

2010-07-01

Policy that targets the school food environment has been advanced as one way to increase the availability of healthy food at schools and healthy food choice by students. Although both state- and district-level policy initiatives have focused on school nutrition standards, it remains to be seen whether these policies translate into healthy food practices at the school level, where student behavior will be impacted. To examine whether state- and district-level nutrition policies addressing junk food in school vending machines and school stores were associated with less junk food in school vending machines and school stores. Junk food was defined as foods and beverages with low nutrient density that provide calories primarily through fats and added sugars. A cross-sectional study design was used to assess self-report data collected by computer-assisted telephone interviews or self-administered mail questionnaires from state-, district-, and school-level respondents participating in the School Health Policies and Programs Study 2006. The School Health Policies and Programs Study, administered every 6 years since 1994 by the Centers for Disease Control and Prevention, is considered the largest, most comprehensive assessment of school health policies and programs in the United States. A nationally representative sample (n=563) of public elementary, middle, and high schools was studied. Logistic regression adjusted for school characteristics, sampling weights, and clustering was used to analyze data. Policies were assessed for strength (required, recommended, neither required nor recommended prohibiting junk food) and whether strength was similar for school vending machines and school stores. School vending machines and school stores were more prevalent in high schools (93%) than middle (84%) and elementary (30%) schools. For state policies, elementary schools that required prohibiting junk food in school vending machines and school stores offered less junk food than elementary schools that neither required nor recommended prohibiting junk food (13% vs 37%; P=0.006). Middle schools that required prohibiting junk food in vending machines and school stores offered less junk food than middle schools that recommended prohibiting junk food (71% vs 87%; P=0.07). Similar associations were not evident for district-level polices or high schools. Policy may be an effective tool to decrease junk food in schools, particularly in elementary and middle schools. Copyright 2010 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

State but not District Nutrition Policies Are Associated with Less Junk Food in Vending Machines and School Stores in US Public Schools

PubMed Central

KUBIK, MARTHA Y.; WALL, MELANIE; SHEN, LIJUAN; NANNEY, MARILYN S.; NELSON, TOBEN F.; LASKA, MELISSA N.; STORY, MARY

2012-01-01

Background Policy that targets the school food environment has been advanced as one way to increase the availability of healthy food at schools and healthy food choice by students. Although both state- and district-level policy initiatives have focused on school nutrition standards, it remains to be seen whether these policies translate into healthy food practices at the school level, where student behavior will be impacted. Objective To examine whether state- and district-level nutrition policies addressing junk food in school vending machines and school stores were associated with less junk food in school vending machines and school stores. Junk food was defined as foods and beverages with low nutrient density that provide calories primarily through fats and added sugars. Design A cross-sectional study design was used to assess self-report data collected by computer-assisted telephone interviews or self-administered mail questionnaires from state-, district-, and school-level respondents participating in the School Health Policies and Programs Study 2006. The School Health Policies and Programs Study, administered every 6 years since 1994 by the Centers for Disease Control and Prevention, is considered the largest, most comprehensive assessment of school health policies and programs in the United States. Subjects/setting A nationally representative sample (n = 563) of public elementary, middle, and high schools was studied. Statistical analysis Logistic regression adjusted for school characteristics, sampling weights, and clustering was used to analyze data. Policies were assessed for strength (required, recommended, neither required nor recommended prohibiting junk food) and whether strength was similar for school vending machines and school stores. Results School vending machines and school stores were more prevalent in high schools (93%) than middle (84%) and elementary (30%) schools. For state policies, elementary schools that required prohibiting junk food in school vending machines and school stores offered less junk food than elementary schools that neither required nor recommended prohibiting junk food (13% vs 37%; P = 0.006). Middle schools that required prohibiting junk food in vending machines and school stores offered less junk food than middle schools that recommended prohibiting junk food (71% vs 87%; P = 0.07). Similar associations were not evident for district-level polices or high schools. Conclusions Policy may be an effective tool to decrease junk food in schools, particularly in elementary and middle schools. PMID:20630161

To select the best tool for generating 3D maintenance data and to set the detailed process for obtaining the 3D maintenance data

NASA Astrophysics Data System (ADS)

Prashanth, B. N.; Roy, Kingshuk

2017-07-01

Three Dimensional (3D) maintenance data provides a link between design and technical documentation creating interactive 3D graphical training and maintenance material. It becomes difficult for an operator to always go through huge paper manuals or come running to the computer for doing maintenance of a machine which makes the maintenance work fatigue. Above being the case, a 3D animation makes maintenance work very simple since, there is no language barrier. The research deals with the generation of 3D maintenance data of any given machine. The best tool for obtaining the 3D maintenance is selected and the tool is analyzed. Using the same tool, a detailed process for extracting the 3D maintenance data for any machine is set. This project aims at selecting the best tool for obtaining 3D maintenance data and to select the detailed process for obtaining 3D maintenance data. 3D maintenance reduces use of big volumes of manuals which creates human errors and makes the work of an operator fatiguing. Hence 3-D maintenance would help in training and maintenance and would increase productivity. 3Dvia when compared with Cortona 3D and Deep Exploration proves to be better than them. 3Dvia is good in data translation and it has the best renderings compared to the other two 3D maintenance software. 3Dvia is very user friendly and it has various options for creating 3D animations. Its Interactive Electronic Technical Publication (IETP) integration is also better than the other two software. Hence 3Dvia proves to be the best software for obtaining 3D maintenance data of any machine.

Swept Mechanism of Micro-Milling Tool Geometry Effect on Machined Oxygen Free High Conductivity Copper (OFHC) Surface Roughness

PubMed Central

Shi, Zhenyu; Liu, Zhanqiang; Li, Yuchao; Qiao, Yang

2017-01-01

Cutting tool geometry should be very much considered in micro-cutting because it has a significant effect on the topography and accuracy of the machined surface, particularly considering the uncut chip thickness is comparable to the cutting edge radius. The objective of this paper was to clarify the influence of the mechanism of the cutting tool geometry on the surface topography in the micro-milling process. Four different cutting tools including two two-fluted end milling tools with different helix angles of 15° and 30° cutting tools, as well as two three-fluted end milling tools with different helix angles of 15° and 30° were investigated by combining theoretical modeling analysis with experimental research. The tool geometry was mathematically modeled through coordinate translation and transformation to make all three cutting edges at the cutting tool tip into the same coordinate system. Swept mechanisms, minimum uncut chip thickness, and cutting tool run-out were considered on modeling surface roughness parameters (the height of surface roughness Rz and average surface roughness Ra) based on the established mathematical model. A set of cutting experiments was carried out using four different shaped cutting tools. It was found that the sweeping volume of the cutting tool increases with the decrease of both the cutting tool helix angle and the flute number. Great coarse machined surface roughness and more non-uniform surface topography are generated when the sweeping volume increases. The outcome of this research should bring about new methodologies for micro-end milling tool design and manufacturing. The machined surface roughness can be improved by appropriately selecting the tool geometrical parameters. PMID:28772479

A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue.

PubMed

Chen, Zhenyu; Li, Jianping; Wei, Liwei

2007-10-01

Recently, gene expression profiling using microarray techniques has been shown as a promising tool to improve the diagnosis and treatment of cancer. Gene expression data contain high level of noise and the overwhelming number of genes relative to the number of available samples. It brings out a great challenge for machine learning and statistic techniques. Support vector machine (SVM) has been successfully used to classify gene expression data of cancer tissue. In the medical field, it is crucial to deliver the user a transparent decision process. How to explain the computed solutions and present the extracted knowledge becomes a main obstacle for SVM. A multiple kernel support vector machine (MK-SVM) scheme, consisting of feature selection, rule extraction and prediction modeling is proposed to improve the explanation capacity of SVM. In this scheme, we show that the feature selection problem can be translated into an ordinary multiple parameters learning problem. And a shrinkage approach: 1-norm based linear programming is proposed to obtain the sparse parameters and the corresponding selected features. We propose a novel rule extraction approach using the information provided by the separating hyperplane and support vectors to improve the generalization capacity and comprehensibility of rules and reduce the computational complexity. Two public gene expression datasets: leukemia dataset and colon tumor dataset are used to demonstrate the performance of this approach. Using the small number of selected genes, MK-SVM achieves encouraging classification accuracy: more than 90% for both two datasets. Moreover, very simple rules with linguist labels are extracted. The rule sets have high diagnostic power because of their good classification performance.

Growth rates and interface shapes in germanium and lead tin telluride observed in-situ, real-time in vertical Bridgman furnaces

NASA Technical Reports Server (NTRS)

Barber, P. G.; Berry, R. F.; Debnam, W. J.; Fripp, A. L.; Woodell, G.; Simchick, R. T.

1995-01-01

Using the advanced technology developed to visualize the melt-solid interface in low Prandtl number materials, crystal growth rates and interface shapes have been measured in germanium and lead tin telluride semiconductors grown in vertical Bridgman furnaces. The experimental importance of using in-situ, real time observations to determine interface shapes, to measure crystal growth rates, and to improve furnace and ampoule designs is demonstrated. The interface shapes observed in-situ, in real-time were verified by quenching and mechanically induced interface demarcation, and they were also confirmed using machined models to ascertain the absence of geometric distortions. Interface shapes depended upon the interface position in the furnace insulation zone, varied with the nature of the crystal being grown, and were dependent on the extent of transition zones at the ends of the ampoule. Actual growth rates varied significantly from the constant translation rate in response to the thermophysical properties of the crystal and its melt and the thermal conditions existing in the furnace at the interface. In the elemental semiconductor germanium the observed rates of crystal growth exceeded the imposed translation rate, but in the compound semiconductor lead tin telluride the observed rates of growth were less than the translation rate. Finally, the extent of ampoule thermal loading influenced the interface positions, the shapes, and the growth rates.

OMV mission simulator

NASA Technical Reports Server (NTRS)

Cok, Keith E.

1989-01-01

The Orbital Maneuvering Vehicle (OMV) will be remotely piloted during rendezvous, docking, or proximity operations with target spacecraft from a ground control console (GCC). The real-time mission simulator and graphics being used to design a console pilot-machine interface are discussed. A real-time orbital dynamics simulator drives the visual displays. The dynamics simulator includes a J2 oblate earth gravity model and a generalized 1962 rotating atmospheric and drag model. The simulator also provides a variable-length communication delay to represent use of the Tracking and Data Relay Satellite System (TDRSS) and NASA Communications (NASCOM). Input parameter files determine the graphics display. This feature allows rapid prototyping since displays can be easily modified from pilot recommendations. A series of pilot reviews are being held to determine an effective pilot-machine interface. Pilots fly missions with nominal to 3-sigma dispersions in translational or rotational axes. Console dimensions, switch type and layout, hand controllers, and graphic interfaces are evaluated by the pilots and the GCC simulator is modified for subsequent runs. Initial results indicate a pilot preference for analog versus digital displays and for two 3-degree-of-freedom hand controllers.

Proteus: a reconfigurable computational network for computer vision

NASA Astrophysics Data System (ADS)

Haralick, Robert M.; Somani, Arun K.; Wittenbrink, Craig M.; Johnson, Robert; Cooper, Kenneth; Shapiro, Linda G.; Phillips, Ihsin T.; Hwang, Jenq N.; Cheung, William; Yao, Yung H.; Chen, Chung-Ho; Yang, Larry; Daugherty, Brian; Lorbeski, Bob; Loving, Kent; Miller, Tom; Parkins, Larye; Soos, Steven L.

1992-04-01

The Proteus architecture is a highly parallel MIMD, multiple instruction, multiple-data machine, optimized for large granularity tasks such as machine vision and image processing The system can achieve 20 Giga-flops (80 Giga-flops peak). It accepts data via multiple serial links at a rate of up to 640 megabytes/second. The system employs a hierarchical reconfigurable interconnection network with the highest level being a circuit switched Enhanced Hypercube serial interconnection network for internal data transfers. The system is designed to use 256 to 1,024 RISC processors. The processors use one megabyte external Read/Write Allocating Caches for reduced multiprocessor contention. The system detects, locates, and replaces faulty subsystems using redundant hardware to facilitate fault tolerance. The parallelism is directly controllable through an advanced software system for partitioning, scheduling, and development. System software includes a translator for the INSIGHT language, a parallel debugger, low and high level simulators, and a message passing system for all control needs. Image processing application software includes a variety of point operators neighborhood, operators, convolution, and the mathematical morphology operations of binary and gray scale dilation, erosion, opening, and closing.

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.

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.

Equivalence of restricted Boltzmann machines and tensor network states

NASA Astrophysics Data System (ADS)

Chen, Jing; Cheng, Song; Xie, Haidong; Wang, Lei; Xiang, Tao

2018-02-01

The restricted Boltzmann machine (RBM) is one of the fundamental building blocks of deep learning. RBM finds wide applications in dimensional reduction, feature extraction, and recommender systems via modeling the probability distributions of a variety of input data including natural images, speech signals, and customer ratings, etc. We build a bridge between RBM and tensor network states (TNS) widely used in quantum many-body physics research. We devise efficient algorithms to translate an RBM into the commonly used TNS. Conversely, we give sufficient and necessary conditions to determine whether a TNS can be transformed into an RBM of given architectures. Revealing these general and constructive connections can cross fertilize both deep learning and quantum many-body physics. Notably, by exploiting the entanglement entropy bound of TNS, we can rigorously quantify the expressive power of RBM on complex data sets. Insights into TNS and its entanglement capacity can guide the design of more powerful deep learning architectures. On the other hand, RBM can represent quantum many-body states with fewer parameters compared to TNS, which may allow more efficient classical simulations.

Assistance System for Disabled People: A Robot Controlled by Blinking and Wireless Link

NASA Astrophysics Data System (ADS)

Del Val, Lara; Jiménez, María I.; Alonso, Alonso; de La Rosa, Ramón; Izquierdo, Alberto; Carrera, Albano

Disabled people already profit from a lot of technical assistance that improves their quality of life. This article presents a system which will allow interaction between a physically disabled person and his environment. This system is controlled by voluntary muscular movements, particularly those of face muscles. These movements will be translated into machine-understandable instructions, and they will be sent by means of a wireless link to a mobile robot that will execute them. Robot includes a video camera, in order to show the user the environment of the route that the robot follows. This system gives a greater personal autonomy to people with reduced mobility.

Programming distributed memory architectures using Kali

NASA Technical Reports Server (NTRS)

Mehrotra, Piyush; Vanrosendale, John

1990-01-01

Programming nonshared memory systems is more difficult than programming shared memory systems, in part because of the relatively low level of current programming environments for such machines. A new programming environment is presented, Kali, which provides a global name space and allows direct access to remote data values. In order to retain efficiency, Kali provides a system on annotations, allowing the user to control those aspects of the program critical to performance, such as data distribution and load balancing. The primitives and constructs provided by the language is described, and some of the issues raised in translating a Kali program for execution on distributed memory systems are also discussed.

Bricklayer Static Analysis

NASA Astrophysics Data System (ADS)

Harris, Christopher

In the U.S., science and math are taking spotlight in education, and rightfully so as they directly impact economic progression. Curiously absent is computer science, which despite its numerous job opportunities and growth does not have as much focus. This thesis develops a source code analysis framework using language translation, and machine learning classifiers to analyze programs written in Bricklayer for the purposes of programmatically identifying relative success or failure of a students Bricklayer program, helping teachers scale in the amount of students they can support, and providing better messaging. The thesis uses as a case study a set of student programs to demonstrate the possibilities of the framework.

Characterization of flexure hinges for the French watt balance experiment

NASA Astrophysics Data System (ADS)

Pinot, Patrick; Genevès, Gérard

2014-08-01

In the French watt balance experiment, the translation and rotation functions must have no backlash, no friction, nor the need for lubricants. In addition errors in position and movement must be below 100 nm. Flexure hinges can meet all of these criteria. Different materials, profile shapes and machining techniques have been studied. The flexure pivots have been characterized using three techniques: 1) an optical microscope and, if necessary, a SEM to observe the surface inhomogeneities; 2) a mass comparator to determine the bending stiffness of unloaded pivots; 3) a loaded beam oscillating freely under vacuum to study the dynamic behavior of loaded pivots.

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

Transmission of chirality through space and across length scales

NASA Astrophysics Data System (ADS)

Morrow, Sarah M.; Bissette, Andrew J.; Fletcher, Stephen P.

2017-05-01

Chirality is a fundamental property and vital to chemistry, biology, physics and materials science. The ability to use asymmetry to operate molecular-level machines or macroscopically functional devices, or to give novel properties to materials, may address key challenges at the heart of the physical sciences. However, how chirality at one length scale can be translated to asymmetry at a different scale is largely not well understood. In this Review, we discuss systems where chiral information is translated across length scales and through space. A variety of synthetic systems involve the transmission of chiral information between the molecular-, meso- and macroscales. We show how fundamental stereochemical principles may be used to design and understand nanoscale chiral phenomena and highlight important recent advances relevant to nanotechnology. The survey reveals that while the study of stereochemistry on the nanoscale is a rich and dynamic area, our understanding of how to control and harness it and dial-up specific properties is still in its infancy. The long-term goal of controlling nanoscale chirality promises to be an exciting journey, revealing insight into biological mechanisms and providing new technologies based on dynamic physical properties.

Shift-, rotation-, and scale-invariant shape recognition system using an optical Hough transform

NASA Astrophysics Data System (ADS)

Schmid, Volker R.; Bader, Gerhard; Lueder, Ernst H.

1998-02-01

We present a hybrid shape recognition system with an optical Hough transform processor. The features of the Hough space offer a separate cancellation of distortions caused by translations and rotations. Scale invariance is also provided by suitable normalization. The proposed system extends the capabilities of Hough transform based detection from only straight lines to areas bounded by edges. A very compact optical design is achieved by a microlens array processor accepting incoherent light as direct optical input and realizing the computationally expensive connections massively parallel. Our newly developed algorithm extracts rotation and translation invariant normalized patterns of bright spots on a 2D grid. A neural network classifier maps the 2D features via a nonlinear hidden layer onto the classification output vector. We propose initialization of the connection weights according to regions of activity specifically assigned to each neuron in the hidden layer using a competitive network. The presented system is designed for industry inspection applications. Presently we have demonstrated detection of six different machined parts in real-time. Our method yields very promising detection results of more than 96% correctly classified parts.

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.

On feature augmentation for semantic argument classification of the Quran English translation using support vector machine

NASA Astrophysics Data System (ADS)

Khaira Batubara, Dina; Arif Bijaksana, Moch; Adiwijaya

2018-03-01

Research on the semantic argument classification requires semantically labeled data in large numbers, called corpus. Because building a corpus is costly and time-consuming, recently many studies have used existing corpus as the training data to conduct semantic argument classification research on new domain. But previous studies have proven that there is a significant decrease in performance when classifying semantic arguments on different domain between the training and the testing data. The main problem is when there is a new argument that found in the testing data but it is not found in the training data. This research carries on semantic argument classification on a new domain that is Quran English Translation by utilizing Propbank corpus as the training data. To recognize the new argument in the training data, this research proposes four new features for extending the argument features in the training data. By using SVM Linear, the experiment has proven that augmenting the proposed features to the baseline system with some combinations option improve the performance of semantic argument classification on Quran data using Propbank Corpus as training data.

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

The Fabric of the Universe: Exploring the Cosmic Web in 3D Prints and Woven Textiles

NASA Astrophysics Data System (ADS)

Diemer, Benedikt; Facio, Isaac

2017-05-01

We introduce The Fabric of the Universe, an art and science collaboration focused on exploring the cosmic web of dark matter with unconventional techniques and materials. We discuss two of our projects in detail. First, we describe a pipeline for translating three-dimensional (3D) density structures from N-body simulations into solid surfaces suitable for 3D printing, and present prints of a cosmological volume and of the infall region around a massive cluster halo. In these models, we discover wall-like features that are invisible in two-dimensional projections. Going beyond the sheer visualization of simulation data, we undertake an exploration of the cosmic web as a three-dimensional woven textile. To this end, we develop experimental 3D weaving techniques to create sphere-like and filamentary shapes and radically simplify a region of the cosmic web into a set of filaments and halos. We translate the resulting tree structure into a series of commands that can be executed by a digital weaving machine, and present a large-scale textile installation.

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion

PubMed Central

Bone, Daniel; Bishop, Somer; Black, Matthew P.; Goodwin, Matthew S.; Lord, Catherine; Narayanan, Shrikanth S.

2016-01-01

Background Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum disorder (ASD) instrument algorithms in an attempt to improve upon widely-used ASD screening and diagnostic tools. Methods The data consisted of Autism Diagnostic Interview-Revised (ADI-R) and Social Responsiveness Scale (SRS) scores for 1,264 verbal individuals with ASD and 462 verbal individuals with non-ASD developmental or psychiatric disorders (DD), split at age 10. Algorithms were created via a robust ML classifier, support vector machine (SVM), while targeting best-estimate clinical diagnosis of ASD vs. non-ASD. Parameter settings were tuned in multiple levels of cross-validation. Results The created algorithms were more effective (higher performing) than current algorithms, were tunable (sensitivity and specificity can be differentially weighted), and were more efficient (achieving near-peak performance with five or fewer codes). Results from ML-based fusion of ADI-R and SRS are reported. We present a screener algorithm for below (above) age 10 that reached 89.2% (86.7%) sensitivity and 59.0% (53.4%) specificity with only five behavioral codes. Conclusions ML is useful for creating robust, customizable instrument algorithms. In a unique dataset comprised of controls with other difficulties, our findings highlight limitations of current caregiver-report instruments and indicate possible avenues for improving ASD screening and diagnostic tools. PMID:27090613

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion.

PubMed

Bone, Daniel; Bishop, Somer L; Black, Matthew P; Goodwin, Matthew S; Lord, Catherine; Narayanan, Shrikanth S

2016-08-01

Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum disorder (ASD) instrument algorithms in an attempt to improve upon widely used ASD screening and diagnostic tools. The data consisted of Autism Diagnostic Interview-Revised (ADI-R) and Social Responsiveness Scale (SRS) scores for 1,264 verbal individuals with ASD and 462 verbal individuals with non-ASD developmental or psychiatric disorders, split at age 10. Algorithms were created via a robust ML classifier, support vector machine, while targeting best-estimate clinical diagnosis of ASD versus non-ASD. Parameter settings were tuned in multiple levels of cross-validation. The created algorithms were more effective (higher performing) than the current algorithms, were tunable (sensitivity and specificity can be differentially weighted), and were more efficient (achieving near-peak performance with five or fewer codes). Results from ML-based fusion of ADI-R and SRS are reported. We present a screener algorithm for below (above) age 10 that reached 89.2% (86.7%) sensitivity and 59.0% (53.4%) specificity with only five behavioral codes. ML is useful for creating robust, customizable instrument algorithms. In a unique dataset comprised of controls with other difficulties, our findings highlight the limitations of current caregiver-report instruments and indicate possible avenues for improving ASD screening and diagnostic tools. © 2016 Association for Child and Adolescent Mental Health.

Function allocation for humans and automation in the context of team dynamics

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

Jeffrey C. Joe; John O'Hara; Jacques Hugo

Within Human Factors Engineering, a decision-making process called function allocation (FA) is used during the design life cycle of complex systems to distribute the system functions, often identified through a functional requirements analysis, to all human and automated machine agents (or teammates) involved in controlling the system. Most FA methods make allocation decisions primarily by comparing the capabilities of humans and automation, but then also by considering secondary factors such as cost, regulations, and the health and safety of workers. The primary analysis of the strengths and weaknesses of humans and machines, however, is almost always considered in terms ofmore » individual human or machine capabilities. Yet, FA is fundamentally about teamwork in that the goal of the FA decision-making process is to determine what are the optimal allocations of functions among agents. Given this framing of FA, and the increasing use of and sophistication of automation, there are two related social psychological issues that current FA methods need to address more thoroughly. First, many principles for effective human teamwork are not considered as central decision points or in the iterative hypothesis and testing phase in most FA methods, when it is clear that social factors have numerous positive and negative effects on individual and team capabilities. Second, social psychological factors affecting team performance and can be difficult to translate to automated agents, and most FA methods currently do not account for this effect. The implications for these issues are discussed.« less

Combined Grinding and Drying of Biomass in One Operation Phase I

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

Sokhansanj, S

2008-06-26

First American Scientific Corporation (FASC) has developed a unique and innovative grinder/dryer called KDS Micronex. The KS (Kinetic Disintegration System) combines two operations of grinding and drying into a single operation which reduces dependence on external heat input. The machine captures the heat of comminution and combines it will centrifugal forces to expedite moisture extraction from wet biomass. Because it uses mechanical forces rather than providing direct heat to perform the drying operation, it is a simpler machine and uses less energy than conventional grinding and drying operations which occur as two separate steps. The entire compact unit can bemore » transported on a flatbed trailer to the site where biomass is available. Hence, the KDS Micronex is a technology that enables inexpensive pretreatment of waste materials and biomass. A well prepared biomass can be used as feed, fuel or fertilizer instead of being discarded. Electricity and chemical feedstock produced from such biomass would displace the use of fossil fuels and no net greenhouse gas emissions would result from such bio-based operations. Organic fertilizers resulting from the KS Micronex grinding/drying process will be pathogen-free unlike raw animal manures. The feasibility tests on KS during Phase I showed that a prototype machine can be developed, field tested and the technology demonstrated for commercial applications. The present KDS machine can remove up to 400 kg/h of water from a wet feed material. Since biomass processors demand a finished product that is only 10% moist and most raw materials like corn stover, bagasse, layer manure, cow dung, and waste wood have moisture contents of the order of 50%, this water removal rate translates to a production rate of roughly half a ton per hour. this is too small for most processors who are unwilling to acquire multiple machines because of the added complexity to the feed and product removal systems. The economics suffer due to small production rates, because the labor costs are a much larger fraction of the production cost. The goal for further research and development work is to scale up the KDS technology incorporating findings from Phase I into a machine that has superior performance characteristics.« less

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.

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.

On the role of exchange of power and information signals in control and stability of the human-robot interaction

NASA Technical Reports Server (NTRS)

Kazerooni, H.

1991-01-01

A human's ability to perform physical tasks is limited, not only by his intelligence, but by his physical strength. If, in an appropriate environment, a machine's mechanical power is closely integrated with a human arm's mechanical power under the control of the human intellect, the resulting system will be superior to a loosely integrated combination of a human and a fully automated robot. Therefore, we must develop a fundamental solution to the problem of 'extending' human mechanical power. The work presented here defines 'extenders' as a class of robot manipulators worn by humans to increase human mechanical strength, while the wearer's intellect remains the central control system for manipulating the extender. The human, in physical contact with the extender, exchanges power and information signals with the extender. The aim is to determine the fundamental building blocks of an intelligent controller, a controller which allows interaction between humans and a broad class of computer-controlled machines via simultaneous exchange of both power and information signals. The prevalent trend in automation has been to physically separate the human from the machine so the human must always send information signals via an intermediary device (e.g., joystick, pushbutton, light switch). Extenders, however are perfect examples of self-powered machines that are built and controlled for the optimal exchange of power and information signals with humans. The human wearing the extender is in physical contact with the machine, so power transfer is unavoidable and information signals from the human help to control the machine. Commands are transferred to the extender via the contact forces and the EMG signals between the wearer and the extender. The extender augments human motor ability without accepting any explicit commands: it accepts the EMG signals and the contact force between the person's arm and the extender, and the extender 'translates' them into a desired position. In this unique configuration, mechanical power transfer between the human and the extender occurs because the human is pushing against the extender. The extender transfers to the human's hand, in feedback fashion, a scaled-down version of the actual external load which the extender is manipulating. This natural feedback force on the human's hand allows him to 'feel' a modified version of the external forces on the extender. The information signals from the human (e.g., EMG signals) to the computer reflect human cognitive ability, and the power transfer between the human and the machine (e.g., physical interaction) reflects human physical ability. Thus the information transfer to the machine augments cognitive ability, and the power transfer augments motor ability. These two actions are coupled through the human cognitive/motor dynamic behavior. The goal is to derive the control rules for a class of computer-controlled machines that augment human physical and cognitive abilities in certain manipulative tasks.

Experimental validation of a distribution theory based analysis of the effect of manufacturing tolerances on permanent magnet synchronous machines

NASA Astrophysics Data System (ADS)

Boscaino, V.; Cipriani, G.; Di Dio, V.; Corpora, M.; Curto, D.; Franzitta, V.; Trapanese, M.

2017-05-01

An experimental study on the effect of permanent magnet tolerances on the performances of a Tubular Linear Ferrite Motor is presented in this paper. The performances that have been investigated are: cogging force, end effect cogging force and generated thrust. It is demonstrated that: 1) the statistical variability of the magnets introduces harmonics in the spectrum of the cogging force; 2) the value of the end effect cogging force is directly linked to the values of then remanence field of the external magnets placed on the slider; 3) the generated thrust and its statistical distribution depend on the remanence field of the magnets placed on the translator.

JPRS report: Science and technology. Central Eurasia: Engineering and equipment

NASA Astrophysics Data System (ADS)

1993-10-01

Translated articles cover the following topics: transient gas dynamic processes in ramjet engines; aerodynamic characteristics of delta wings with detached leading edge shock wave at hypersonic flight velocities; effect of atmospheric density gradient on aerodynamic stabilization; measurement of target radar scattering characteristics using frequency synthesized signals; assessing survivability and ensuring safety of large axial-flow compressor blades; procedure for experimentally determining transient aerodynamic forces caused by flat vane cascade; analysis of aerodynamic interaction of profile and vortex; laser machine for balancing dynamically adjusted gyros; use of heat pumps in solar heat supply systems; numerical simulation of deflagration transition to detonation in homogeneous combustible fuel mixture; and investigation of chemically nonequilibrium flow about bodies allowing for vibrational relaxation.

Ribosomes: Ribozymes that Survived Evolution Pressures but Is Paralyzed by Tiny Antibiotics

NASA Astrophysics Data System (ADS)

Yonath, Ada

An impressive number of crystal structures of ribosomes, the universal cellular machines that translate the genetic code into proteins, emerged during the last decade. The determination of ribosome high resolution structure, which was widely considered formidable, led to novel insights into the ribosomal function, namely, fidelity, catalytic mechanism, and polymerize activities. They also led to suggestions concerning its origin and shed light on the action, selectivity and synergism of ribosomal antibiotics; illuminated mechanisms acquiring bacterial resistance and provided structural information for drug improvement and design. These studies required the pioneering and implementation of advanced technologies, which directly influenced the remarkable increase of the number of structures deposited in the Protein Data Bank.

Leveraging Paraphrase Labels to Extract Synonyms from Twitter

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

Antoniak, Maria A.; Bell, Eric B.; Xia, Fei

2015-05-18

We present an approach for automatically learning synonyms from a paraphrase corpus of tweets. This work shows improvement on the task of paraphrase detection when we substitute our extracted synonyms into the training set. The synonyms are learned by using chunks from a shallow parse to create candidate synonyms and their context windows, and the synonyms are incorporated into a paraphrase detection system that uses machine translation metrics as features for a classifier. We demonstrate a 2.29% improvement in F1 when we train and test on the paraphrase training set, providing better coverage than previous systems, which shows the potentialmore » power of synonyms that are representative of a specific topic.« less

The Design of Large High-Speed Wind Tunnels

DTIC Science & Technology

1954-05-04

w 0 U- Y . CC U 0 cr0 o 0 0. ZW3 0 0 -H N Io~ D) 4-) ao 4.) 0 0 0 4 0 00 I, w O 0r M CL 2~ H 0 z U) F - l < C 0 00r I = I-00 L 0 z wI0 a 0474 ) caa 0 w...walls being straight and parallel. 0 0 n u .. . It has been found that translation of the lower wall results in a 0 simplified mechanical design. The...provides simpler rotor construction with apparently no great sacrifice in performance for a machine of relatively low pressure rise per stage. 0 1P| n

USSR Space Life Sciences Digest, issue 1

NASA Technical Reports Server (NTRS)

Hooke, L. R.; Radtke, M.; Rowe, J. E.

1985-01-01

The first issue of the bimonthly digest of USSR Space Life Sciences is presented. Abstracts are included for 49 Soviet periodical articles in 19 areas of aerospace medicine and space biology, published in Russian during the first quarter of 1985. Translated introductions and table of contents for nine Russian books on topics related to NASA's life science concerns are presented. Areas covered include: botany, cardiovascular and respiratory systems, cybernetics and biomedical data processing, endocrinology, gastrointestinal system, genetics, group dynamics, habitability and environmental effects, health and medicine, hematology, immunology, life support systems, man machine systems, metabolism, musculoskeletal system, neurophysiology, perception, personnel selection, psychology, radiobiology, reproductive system, and space biology. This issue concentrates on aerospace medicine and space biology.

Generating description with multi-feature fusion and saliency maps of image

NASA Astrophysics Data System (ADS)

Liu, Lisha; Ding, Yuxuan; Tian, Chunna; Yuan, Bo

2018-04-01

Generating description for an image can be regard as visual understanding. It is across artificial intelligence, machine learning, natural language processing and many other areas. In this paper, we present a model that generates description for images based on RNN (recurrent neural network) with object attention and multi-feature of images. The deep recurrent neural networks have excellent performance in machine translation, so we use it to generate natural sentence description for images. The proposed method uses single CNN (convolution neural network) that is trained on ImageNet to extract image features. But we think it can not adequately contain the content in images, it may only focus on the object area of image. So we add scene information to image feature using CNN which is trained on Places205. Experiments show that model with multi-feature extracted by two CNNs perform better than which with a single feature. In addition, we make saliency weights on images to emphasize the salient objects in images. We evaluate our model on MSCOCO based on public metrics, and the results show that our model performs better than several state-of-the-art methods.

A possible extension to the RInChI as a means of providing machine readable process data.

PubMed

Jacob, Philipp-Maximilian; Lan, Tian; Goodman, Jonathan M; Lapkin, Alexei A

2017-04-11

The algorithmic, large-scale use and analysis of reaction databases such as Reaxys is currently hindered by the absence of widely adopted standards for publishing reaction data in machine readable formats. Crucial data such as yields of all products or stoichiometry are frequently not explicitly stated in the published papers and, hence, not reported in the database entry for those reactions, limiting their usefulness for algorithmic analysis. This paper presents a possible extension to the IUPAC RInChI standard via an auxiliary layer, termed ProcAuxInfo, which is a standardised, extensible form in which to report certain key reaction parameters such as declaration of all products and reactants as well as auxiliaries known in the reaction, reaction stoichiometry, amounts of substances used, conversion, yield and operating conditions. The standard is demonstrated via creation of the RInChI including the ProcAuxInfo layer based on three published reactions and demonstrates accurate data recoverability via reverse translation of the created strings. Implementation of this or another method of reporting process data by the publishing community would ensure that databases, such as Reaxys, would be able to abstract crucial data for big data analysis of their contents.

Analysis of the fluid mechanical sewing machine

NASA Astrophysics Data System (ADS)

Brun, Pierre-Thomas; Audoly, Basile; Ribe, Neil

2012-02-01

A thin thread of viscous fluid falling onto a moving belt generates a surprising variety of patterns, similar to the stitch patterns produced by a traditional sewing machine. By simulating the dynamics of the viscous thread numerically, we can reproduce these patterns and their bifurcations. The results lead us to propose a new classification of the stitch patterns within a unified framework, based on the Fourier spectra of the motion of the point of contact of the thread with the belt. The frequencies of the longitudinal and transverse components of the contact point motion are locked in most cases to simple ratios of the frequency φc of steady coiling on a surface at rest (i.e., the limit of zero belt speed). In particular, the ``alternating loops'' pattern involves the first five multiples of φc/3. The dynamics of the patterns can be described by matching the upper (linear) and the lower (non-linear) portions of the thread. Following this path we propose a toy model that successfully reproduces the observed transitions from the steady dragged configuration to sinusoidal meanders, alternating loops, and the translated coiling pattern as the belt speed is varied.

Virtual Machine Language

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

Resistance gene identification from Larimichthys crocea with machine learning techniques

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

Elements of a next generation time-series ASCII data file format for Earth Sciences

NASA Astrophysics Data System (ADS)

Webster, C. J.

2015-12-01

Data in ASCII comma separated value (CSV) format are recognized as the most simple, straightforward and readable type of data present in the geosciences. Many scientific workflows developed over the years rely on data using this simple format. However, there is a need for a lightweight ASCII header format standard that is easy to create and easy to work with. Current OGC grade XML standards are complex and difficult to implement for researchers with few resources. Ideally, such a format should provide the data in CSV for easy consumption by generic applications such as spreadsheets. The format should use an existing time standard. The header should be easily human readable as well as machine parsable. The metadata format should be extendable to allow vocabularies to be adopted as they are created by external standards bodies. The creation of such a format will increase the productivity of software engineers and scientists because fewer translators and checkers would be required. Data in ASCII comma separated value (CSV) format are recognized as the most simple, straightforward and readable type of data present in the geosciences. Many scientific workflows developed over the years rely on data using this simple format. However, there is a need for a lightweight ASCII header format standard that is easy to create and easy to work with. Current OGC grade XML standards are complex and difficult to implement for researchers with few resources. Ideally, such a format would provide the data in CSV for easy consumption by generic applications such as spreadsheets. The format would use existing time standard. The header would be easily human readable as well as machine parsable. The metadata format would be extendable to allow vocabularies to be adopted as they are created by external standards bodies. The creation of such a format would increase the productivity of software engineers and scientists because fewer translators would be required.

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.

Cryptic out-of-frame translational initiation of TBCE rescues tubulin formation in compound heterozygous HRD.

PubMed

Tian, Guoling; Huang, Melissa C; Parvari, Ruti; Diaz, George A; Cowan, Nicholas J

2006-09-05

Microtubules are indispensable dynamic structures that contribute to many essential biological functions. Assembly of the native alpha/beta tubulin heterodimer, the subunit that polymerizes to form microtubules, requires the participation of several molecular chaperones, namely prefoldin, the cytosolic chaperonin CCT, and a series of five tubulin-specific chaperones termed cofactors A-E (TBCA-E). Among these, TBCC, TBCD, and TBCE are essential in higher eukaryotes; they function together as a multimolecular machine that assembles quasinative CCT-generated alpha- and beta-tubulin polypeptides into new heterodimers. Deletion and truncation mutations in the gene encoding TBCE have been shown to cause the rare autosomal recessive syndrome known as HRD, a devastating disorder characterized by congenital hypoparathyroidism, mental retardation, facial dysmorphism, and extreme growth failure. Here we identify cryptic translational initiation at each of three out-of-frame AUG codons upstream of the genetic lesion as a unique mechanism that rescues a mutant HRD allele by producing a functional TBCE protein. Our data explain how afflicted individuals, who would otherwise lack the capacity to make functional TBCE, can survive and point to a limiting capacity to fold tubulin heterodimers de novo as a contributing factor to disease pathogenesis.

Cryptic out-of-frame translational initiation of TBCE rescues tubulin formation in compound heterozygous HRD

PubMed Central

Tian, Guoling; Huang, Melissa C.; Parvari, Ruti; Diaz, George A.; Cowan, Nicholas J.

2006-01-01

Microtubules are indispensable dynamic structures that contribute to many essential biological functions. Assembly of the native α/β tubulin heterodimer, the subunit that polymerizes to form microtubules, requires the participation of several molecular chaperones, namely prefoldin, the cytosolic chaperonin CCT, and a series of five tubulin-specific chaperones termed cofactors A–E (TBCA–E). Among these, TBCC, TBCD, and TBCE are essential in higher eukaryotes; they function together as a multimolecular machine that assembles quasinative CCT-generated α- and β-tubulin polypeptides into new heterodimers. Deletion and truncation mutations in the gene encoding TBCE have been shown to cause the rare autosomal recessive syndrome known as HRD, a devastating disorder characterized by congenital hypoparathyroidism, mental retardation, facial dysmorphism, and extreme growth failure. Here we identify cryptic translational initiation at each of three out-of-frame AUG codons upstream of the genetic lesion as a unique mechanism that rescues a mutant HRD allele by producing a functional TBCE protein. Our data explain how afflicted individuals, who would otherwise lack the capacity to make functional TBCE, can survive and point to a limiting capacity to fold tubulin heterodimers de novo as a contributing factor to disease pathogenesis. PMID:16938882

The BCI competition. III: Validating alternative approaches to actual BCI problems.

PubMed

Blankertz, Benjamin; Müller, Klaus-Robert; Krusienski, Dean J; Schalk, Gerwin; Wolpaw, Jonathan R; Schlögl, Alois; Pfurtscheller, Gert; Millán, José del R; Schröder, Michael; Birbaumer, Niels

2006-06-01

A brain-computer interface (BCI) is a system that allows its users to control external devices with brain activity. Although the proof-of-concept was given decades ago, the reliable translation of user intent into device control commands is still a major challenge. Success requires the effective interaction of two adaptive controllers: the user's brain, which produces brain activity that encodes intent, and the BCI system, which translates that activity into device control commands. In order to facilitate this interaction, many laboratories are exploring a variety of signal analysis techniques to improve the adaptation of the BCI system to the user. In the literature, many machine learning and pattern classification algorithms have been reported to give impressive results when applied to BCI data in offline analyses. However, it is more difficult to evaluate their relative value for actual online use. BCI data competitions have been organized to provide objective formal evaluations of alternative methods. Prompted by the great interest in the first two BCI Competitions, we organized the third BCI Competition to address several of the most difficult and important analysis problems in BCI research. The paper describes the data sets that were provided to the competitors and gives an overview of the results.

IRESPred: Web Server for Prediction of Cellular and Viral Internal Ribosome Entry Site (IRES)

PubMed Central

Kolekar, Pandurang; Pataskar, Abhijeet; Kulkarni-Kale, Urmila; Pal, Jayanta; Kulkarni, Abhijeet

2016-01-01

Cellular mRNAs are predominantly translated in a cap-dependent manner. However, some viral and a subset of cellular mRNAs initiate their translation in a cap-independent manner. This requires presence of a structured RNA element, known as, Internal Ribosome Entry Site (IRES) in their 5′ untranslated regions (UTRs). Experimental demonstration of IRES in UTR remains a challenging task. Computational prediction of IRES merely based on sequence and structure conservation is also difficult, particularly for cellular IRES. A web server, IRESPred is developed for prediction of both viral and cellular IRES using Support Vector Machine (SVM). The predictive model was built using 35 features that are based on sequence and structural properties of UTRs and the probabilities of interactions between UTR and small subunit ribosomal proteins (SSRPs). The model was found to have 75.51% accuracy, 75.75% sensitivity, 75.25% specificity, 75.75% precision and Matthews Correlation Coefficient (MCC) of 0.51 in blind testing. IRESPred was found to perform better than the only available viral IRES prediction server, VIPS. The IRESPred server is freely available at http://bioinfo.net.in/IRESPred/. PMID:27264539

Many-Body Descriptors for Predicting Molecular Properties with Machine Learning: Analysis of Pairwise and Three-Body Interactions in Molecules.

PubMed

Pronobis, Wiktor; Tkatchenko, Alexandre; Müller, Klaus-Robert

2018-06-12

Machine learning (ML) based prediction of molecular properties across chemical compound space is an important and alternative approach to efficiently estimate the solutions of highly complex many-electron problems in chemistry and physics. Statistical methods represent molecules as descriptors that should encode molecular symmetries and interactions between atoms. Many such descriptors have been proposed; all of them have advantages and limitations. Here, we propose a set of general two-body and three-body interaction descriptors which are invariant to translation, rotation, and atomic indexing. By adapting the successfully used kernel ridge regression methods of machine learning, we evaluate our descriptors on predicting several properties of small organic molecules calculated using density-functional theory. We use two data sets. The GDB-7 set contains 6868 molecules with up to 7 heavy atoms of type CNO. The GDB-9 set is composed of 131722 molecules with up to 9 heavy atoms containing CNO. When trained on 5000 random molecules, our best model achieves an accuracy of 0.8 kcal/mol (on the remaining 1868 molecules of GDB-7) and 1.5 kcal/mol (on the remaining 126722 molecules of GDB-9) respectively. Applying a linear regression model on our novel many-body descriptors performs almost equal to a nonlinear kernelized model. Linear models are readily interpretable: a feature importance ranking measure helps to obtain qualitative and quantitative insights on the importance of two- and three-body molecular interactions for predicting molecular properties computed with quantum-mechanical methods.

Application of Machine Learning to Predict Dietary Lapses During Weight Loss.

PubMed

Goldstein, Stephanie P; Zhang, Fengqing; Thomas, John G; Butryn, Meghan L; Herbert, James D; Forman, Evan M

2018-05-01

Individuals who adhere to dietary guidelines provided during weight loss interventions tend to be more successful with weight control. Any deviation from dietary guidelines can be referred to as a "lapse." There is a growing body of research showing that lapses are predictable using a variety of physiological, environmental, and psychological indicators. With recent technological advancements, it may be possible to assess these triggers and predict dietary lapses in real time. The current study sought to use machine learning techniques to predict lapses and evaluate the utility of combining both group- and individual-level data to enhance lapse prediction. The current study trained and tested a machine learning algorithm capable of predicting dietary lapses from a behavioral weight loss program among adults with overweight/obesity (n = 12). Participants were asked to follow a weight control diet for 6 weeks and complete ecological momentary assessment (EMA; repeated brief surveys delivered via smartphone) regarding dietary lapses and relevant triggers. WEKA decision trees were used to predict lapses with an accuracy of 0.72 for the group of participants. However, generalization of the group algorithm to each individual was poor, and as such, group- and individual-level data were combined to improve prediction. The findings suggest that 4 weeks of individual data collection is recommended to attain optimal model performance. The predictive algorithm could be utilized to provide in-the-moment interventions to prevent dietary lapses and therefore enhance weight losses. Furthermore, methods in the current study could be translated to other types of health behavior lapses.

Bridging a translational gap: using machine learning to improve the prediction of PTSD.

PubMed

Karstoft, Karen-Inge; Galatzer-Levy, Isaac R; Statnikov, Alexander; Li, Zhiguo; Shalev, Arieh Y

2015-03-16

Predicting Posttraumatic Stress Disorder (PTSD) is a pre-requisite for targeted prevention. Current research has identified group-level risk-indicators, many of which (e.g., head trauma, receiving opiates) concern but a subset of survivors. Identifying interchangeable sets of risk indicators may increase the efficiency of early risk assessment. The study goal is to use supervised machine learning (ML) to uncover interchangeable, maximally predictive combinations of early risk indicators. Data variables (features) reflecting event characteristics, emergency department (ED) records and early symptoms were collected in 957 trauma survivors within ten days of ED admission, and used to predict PTSD symptom trajectories during the following fifteen months. A Target Information Equivalence Algorithm (TIE*) identified all minimal sets of features (Markov Boundaries; MBs) that maximized the prediction of a non-remitting PTSD symptom trajectory when integrated in a support vector machine (SVM). The predictive accuracy of each set of predictors was evaluated in a repeated 10-fold cross-validation and expressed as average area under the Receiver Operating Characteristics curve (AUC) for all validation trials. The average number of MBs per cross validation was 800. MBs' mean AUC was 0.75 (95% range: 0.67-0.80). The average number of features per MB was 18 (range: 12-32) with 13 features present in over 75% of the sets. Our findings support the hypothesized existence of multiple and interchangeable sets of risk indicators that equally and exhaustively predict non-remitting PTSD. ML's ability to increase prediction versatility is a promising step towards developing algorithmic, knowledge-based, personalized prediction of post-traumatic psychopathology.

An Investigation of the Relationship Between Automated Machine Translation Evaluation Metrics and User Performance on an Information Extraction Task

DTIC Science & Technology

2007-01-01

parameter dimension between the two models). 93 were tested.3 Model 1 log( pHits 1− pHits ) = α + β1 ∗ MetricScore (6.6) The results for each of the...505.67 oTERavg .357 .13 .007 log( pHits 1− pHits ), that is, log-odds of correct task performance, of 2.79 over the intercept only model. All... pHits 1− pHits ) = −1.15− .418× I[MT=2] − .527× I[MT=3] + 1.78×METEOR+ 1.28×METEOR × I[MT=2] + 1.86×METEOR × I[MT=3] (6.7) Model 3 log( pHits 1− pHits

An operational system for subject switching between controlled vocabularies

NASA Technical Reports Server (NTRS)

Silvester, June P.; Klingbiel, Paul H.

1993-01-01

The NASA system of automatically converting sets of terms assigned by Department of Defense indexers to sets of NASA's authorized terms is described. This little-touted system, which has been operating successfully since 1983, matches concepts, rather than words. Subject Switching uses a translation table, known as the Lexical Dictionary, accessed by a program that determines which rules to follow in making the transition from DTIC's to NASA's authorized terms. The authors describe the four phases of development of Subject Switching, changes that have been made, evaluating the system, and benefits. Benefits to NASA include saving indexers' time, the addition of access points for documents indexed, the utilization of other government indexing, and a contribution towards the now-operational NASA, online, interactive, machine aided indexing.

Model Considerations for Memory-based Automatic Music Transcription

NASA Astrophysics Data System (ADS)

Albrecht, Štěpán; Šmídl, Václav

2009-12-01

The problem of automatic music description is considered. The recorded music is modeled as a superposition of known sounds from a library weighted by unknown weights. Similar observation models are commonly used in statistics and machine learning. Many methods for estimation of the weights are available. These methods differ in the assumptions imposed on the weights. In Bayesian paradigm, these assumptions are typically expressed in the form of prior probability density function (pdf) on the weights. In this paper, commonly used assumptions about music signal are summarized and complemented by a new assumption. These assumptions are translated into pdfs and combined into a single prior density using combination of pdfs. Validity of the model is tested in simulation using synthetic data.

Policy Process Editor for P3BM Software

NASA Technical Reports Server (NTRS)

James, Mark; Chang, Hsin-Ping; Chow, Edward T.; Crichton, Gerald A.

2010-01-01

A computer program enables generation, in the form of graphical representations of process flows with embedded natural-language policy statements, input to a suite of policy-, process-, and performance-based management (P3BM) software. This program (1) serves as an interface between users and the Hunter software, which translates the input into machine-readable form; and (2) enables users to initialize and monitor the policy-implementation process. This program provides an intuitive graphical interface for incorporating natural-language policy statements into business-process flow diagrams. Thus, the program enables users who dictate policies to intuitively embed their intended process flows as they state the policies, reducing the likelihood of errors and reducing the time between declaration and execution of policy.

Programming languages and compiler design for realistic quantum hardware.

PubMed

Chong, Frederic T; Franklin, Diana; Martonosi, Margaret

2017-09-13

Quantum computing sits at an important inflection point. For years, high-level algorithms for quantum computers have shown considerable promise, and recent advances in quantum device fabrication offer hope of utility. A gap still exists, however, between the hardware size and reliability requirements of quantum computing algorithms and the physical machines foreseen within the next ten years. To bridge this gap, quantum computers require appropriate software to translate and optimize applications (toolflows) and abstraction layers. Given the stringent resource constraints in quantum computing, information passed between layers of software and implementations will differ markedly from in classical computing. Quantum toolflows must expose more physical details between layers, so the challenge is to find abstractions that expose key details while hiding enough complexity.

The Language Grid: supporting intercultural collaboration

NASA Astrophysics Data System (ADS)

Ishida, T.

2018-03-01

A variety of language resources already exist online. Unfortunately, since many language resources have usage restrictions, it is virtually impossible for each user to negotiate with every language resource provider when combining several resources to achieve the intended purpose. To increase the accessibility and usability of language resources (dictionaries, parallel texts, part-of-speech taggers, machine translators, etc.), we proposed the Language Grid [1]; it wraps existing language resources as atomic services and enables users to create new services by combining the atomic services, and reduces the negotiation costs related to intellectual property rights [4]. Our slogan is “language services from language resources.” We believe that modularization with recombination is the key to creating a full range of customized language environments for various user communities.

Laser reflectance measurement for the online monitoring of Chlorella sorokiniana biomass concentration.

PubMed

López Expósito, Patricio; Blanco Suárez, Angeles; Negro Álvarez, Carlos

2017-02-10

Fast and reliable methods to determine biomass concentration are necessary to facilitate the large scale production of microalgae. A method for the rapid estimation of Chlorella sorokiniana biomass concentration was developed. The method translates the suspension particle size spectrum gathered though laser reflectance into biomass concentration by means of two machine learning modelling techniques. In each case, the model hyper-parameters were selected applying a simulated annealing algorithm. The results show that dry biomass concentration can be estimated with a very good accuracy (R 2 =0.87). The presented method seems to be suited to perform fast estimations of biomass concentration in suspensions of microalgae cultivated in moderately turbid media with tendency to aggregate. Copyright © 2017 Elsevier B.V. All rights reserved.

[Microcomputer control of a LED stimulus display device].

PubMed

Ohmoto, S; Kikuchi, T; Kumada, T

1987-02-01

A visual stimulus display system controlled by a microcomputer was constructed at low cost. The system consists of a LED stimulus display device, a microcomputer, two interface boards, a pointing device (a "mouse") and two kinds of software. The first software package is written in BASIC. Its functions are: to construct stimulus patterns using the mouse, to construct letter patterns (alphabet, digit, symbols and Japanese letters--kanji, hiragana, katakana), to modify the patterns, to store the patterns on a floppy disc, to translate the patterns into integer data which are used to display the patterns in the second software. The second software package, written in BASIC and machine language, controls display of a sequence of stimulus patterns in predetermined time schedules in visual experiments.

Multi-dimensional position sensor using range detectors

DOEpatents

Vann, Charles S.

2000-01-01

A small, non-contact optical sensor uses ranges and images to detect its relative position to an object in up to six degrees of freedom. The sensor has three light emitting range detectors which illuminate a target and can be used to determine distance and two tilt angles. A camera located between the three range detectors senses the three remaining degrees of freedom, two translations and one rotation. Various range detectors, with different light sources, e.g. lasers and LEDs, different collection options, and different detection schemes, e.g. diminishing return and time of flight can be used. This sensor increases the capability and flexibility of computer controlled machines, e.g. it can instruct a robot how to adjust automatically to different positions and orientations of a part.

Programming languages and compiler design for realistic quantum hardware

NASA Astrophysics Data System (ADS)

Chong, Frederic T.; Franklin, Diana; Martonosi, Margaret

2017-09-01

Quantum computing sits at an important inflection point. For years, high-level algorithms for quantum computers have shown considerable promise, and recent advances in quantum device fabrication offer hope of utility. A gap still exists, however, between the hardware size and reliability requirements of quantum computing algorithms and the physical machines foreseen within the next ten years. To bridge this gap, quantum computers require appropriate software to translate and optimize applications (toolflows) and abstraction layers. Given the stringent resource constraints in quantum computing, information passed between layers of software and implementations will differ markedly from in classical computing. Quantum toolflows must expose more physical details between layers, so the challenge is to find abstractions that expose key details while hiding enough complexity.

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

Prediction of plant pre-microRNAs and their microRNAs in genome-scale sequences using structure-sequence features and support vector machine.

PubMed

Meng, Jun; Liu, Dong; Sun, Chao; Luan, Yushi

2014-12-30

MicroRNAs (miRNAs) are a family of non-coding RNAs approximately 21 nucleotides in length that play pivotal roles at the post-transcriptional level in animals, plants and viruses. These molecules silence their target genes by degrading transcription or suppressing translation. Studies have shown that miRNAs are involved in biological responses to a variety of biotic and abiotic stresses. Identification of these molecules and their targets can aid the understanding of regulatory processes. Recently, prediction methods based on machine learning have been widely used for miRNA prediction. However, most of these methods were designed for mammalian miRNA prediction, and few are available for predicting miRNAs in the pre-miRNAs of specific plant species. Although the complete Solanum lycopersicum genome has been published, only 77 Solanum lycopersicum miRNAs have been identified, far less than the estimated number. Therefore, it is essential to develop a prediction method based on machine learning to identify new plant miRNAs. A novel classification model based on a support vector machine (SVM) was trained to identify real and pseudo plant pre-miRNAs together with their miRNAs. An initial set of 152 novel features related to sequential structures was used to train the model. By applying feature selection, we obtained the best subset of 47 features for use with the Back Support Vector Machine-Recursive Feature Elimination (B-SVM-RFE) method for the classification of plant pre-miRNAs. Using this method, 63 features were obtained for plant miRNA classification. We then developed an integrated classification model, miPlantPreMat, which comprises MiPlantPre and MiPlantMat, to identify plant pre-miRNAs and their miRNAs. This model achieved approximately 90% accuracy using plant datasets from nine plant species, including Arabidopsis thaliana, Glycine max, Oryza sativa, Physcomitrella patens, Medicago truncatula, Sorghum bicolor, Arabidopsis lyrata, Zea mays and Solanum lycopersicum. Using miPlantPreMat, 522 Solanum lycopersicum miRNAs were identified in the Solanum lycopersicum genome sequence. We developed an integrated classification model, miPlantPreMat, based on structure-sequence features and SVM. MiPlantPreMat was used to identify both plant pre-miRNAs and the corresponding mature miRNAs. An improved feature selection method was proposed, resulting in high classification accuracy, sensitivity and specificity.

The strategic offense initiative? The Soviets and Star Wars

NASA Astrophysics Data System (ADS)

Westwick, Peter J.

2014-05-01

Historians of the Cold War have paid too little attention to Soviet fears of "space-strike weapons" - that is, possible offensive uses of President Ronald Reagan's Strategic Defense Initiative. In fifteen years or so, soldiers will no longer shoot rifles but will use some kind of lightning, some sort of a machine emitting a holocaustal electrical beam. Tell me, what can we invent in this line so as to surprise our neighbors?... Alas, we are only capable of imitating and purchasing weapons from others, and we do well if we manage to repair them ourselves. --Fyodor Dostoevsky, A Writer's Diary, 1873. [Khlinov, a physicist]: "I know that he has made an important discovery concerning the transmission of infra-red rays over a distance.... Heat waves at a temperature of a thousand degrees centigrade transmitted parallel to each other constitute a monstrous weapon of destruction and defense in time of war. The whole secret lies in the transmission of a ray that does not disperse. So far nobody has been able to do this. Judging by your story, Garin has constructed a machine that will do it. If so it is an extremely important discovery." "I've been thinking for a long time that this invention smells of higher politics," said Shelga. --Aleksei Tolstoy, The Garin Death Ray, 1927 (translated by George Hanna)

Rama: a machine learning approach for ribosomal protein prediction in plants.

PubMed

Carvalho, Thales Francisco Mota; Silva, José Cleydson F; Calil, Iara Pinheiro; Fontes, Elizabeth Pacheco Batista; Cerqueira, Fabio Ribeiro

2017-11-24

Ribosomal proteins (RPs) play a fundamental role within all type of cells, as they are major components of ribosomes, which are essential for translation of mRNAs. Furthermore, these proteins are involved in various physiological and pathological processes. The intrinsic biological relevance of RPs motivated advanced studies for the identification of unrevealed RPs. In this work, we propose a new computational method, termed Rama, for the prediction of RPs, based on machine learning techniques, with a particular interest in plants. To perform an effective classification, Rama uses a set of fundamental attributes of the amino acid side chains and applies a two-step procedure to classify proteins with unknown function as RPs. The evaluation of the resultant predictive models showed that Rama could achieve mean sensitivity, precision, and specificity of 0.91, 0.91, and 0.82, respectively. Furthermore, a list of proteins that have no annotation in Phytozome v.10, and are annotated as RPs in Phytozome v.12, were correctly classified by our models. Additional computational experiments have also shown that Rama presents high accuracy to differentiate ribosomal proteins from RNA-binding proteins. Finally, two novel proteins of Arabidopsis thaliana were validated in biological experiments. Rama is freely available at http://inctipp.bioagro.ufv.br:8080/Rama .

Polar bears, antibiotics, and the evolving ribosome (Nobel Lecture).

PubMed

Yonath, Ada

2010-06-14

High-resolution structures of ribosomes, the cellular machines that translate the genetic code into proteins, revealed the decoding mechanism, detected the mRNA path, identified the sites of the tRNA molecules in the ribosome, elucidated the position and the nature of the nascent proteins exit tunnel, illuminated the interactions of the ribosome with non-ribosomal factors, such as the initiation, release and recycling factors, and provided valuable information on ribosomal antibiotics, their binding sites, modes of action, principles of selectivity and the mechanisms leading to their resistance. Notably, these structures proved that the ribosome is a ribozyme whose active site, namely where the peptide bonds are being formed, is situated within a universal symmetrical region that is embedded in the otherwise asymmetric ribosome structure. As this symmetrical region is highly conserved and provides the machinery required for peptide bond formation and for ribosome polymerase activity, it may be the remnant of the proto-ribosome, a dimeric prebiotic machine that formed peptide bonds and non-coded polypeptide chains. Structures of complexes of ribosomes with antibiotics targeting them revealed the principles allowing for their clinical use, identified resistance mechanisms and showed the structural bases for discriminating pathogenic bacteria from hosts, hence providing valuable structural information for antibiotics improvement and for the design of novel compounds that can serve as antibiotics.

A support vector machine model provides an accurate transcript-level-based diagnostic for major depressive disorder

PubMed Central

Yu, J S; Xue, A Y; Redei, E E; Bagheri, N

2016-01-01

Major depressive disorder (MDD) is a critical cause of morbidity and disability with an economic cost of hundreds of billions of dollars each year, necessitating more effective treatment strategies and novel approaches to translational research. A notable barrier in addressing this public health threat involves reliable identification of the disorder, as many affected individuals remain undiagnosed or misdiagnosed. An objective blood-based diagnostic test using transcript levels of a panel of markers would provide an invaluable tool for MDD as the infrastructure—including equipment, trained personnel, billing, and governmental approval—for similar tests is well established in clinics worldwide. Here we present a supervised classification model utilizing support vector machines (SVMs) for the analysis of transcriptomic data readily obtained from a peripheral blood specimen. The model was trained on data from subjects with MDD (n=32) and age- and gender-matched controls (n=32). This SVM model provides a cross-validated sensitivity and specificity of 90.6% for the diagnosis of MDD using a panel of 10 transcripts. We applied a logistic equation on the SVM model and quantified a likelihood of depression score. This score gives the probability of a MDD diagnosis and allows the tuning of specificity and sensitivity for individual patients to bring personalized medicine closer in psychiatry. PMID:27779627

Use of statecharts in the modelling of dynamic behaviour in the ATLAS DAQ prototype-1

NASA Astrophysics Data System (ADS)

Croll, P.; Duval, P.-Y.; Jones, R.; Kolos, S.; Sari, R. F.; Wheeler, S.

1998-08-01

Many applications within the ATLAS DAQ prototype-1 system have complicated dynamic behaviour which can be successfully modelled in terms of states and transitions between states. Previously, state diagrams implemented as finite-state machines have been used. Although effective, they become ungainly as system size increases. Harel statecharts address this problem by implementing additional features such as hierarchy and concurrency. The CHSM object-oriented language system is freeware which implements Harel statecharts as concurrent, hierarchical, finite-state machines (CHSMs). An evaluation of this language system by the ATLAS DAQ group has shown it to be suitable for describing the dynamic behaviour of typical DAQ applications. The language is currently being used to model the dynamic behaviour of the prototype-1 run-control system. The design is specified by means of a CHSM description file, and C++ code is obtained by running the CHSM compiler on the file. In parallel with the modelling work, a code generator has been developed which translates statecharts, drawn using the StP CASE tool, into the CHSM language. C++ code, describing the dynamic behaviour of the run-control system, has been successfully generated directly from StP statecharts using the CHSM generator and compiler. The validity of the design was tested using the simulation features of the Statemate CASE tool.

Overview and recent results of the Magnetized Shock Experiment (MSX)

NASA Astrophysics Data System (ADS)

Weber, T. E.; Smith, R. J.; Hsu, S. C.; Omelchenko, Y.

2015-11-01

Recent machine and diagnostics upgrades to the Magnetized Shock Experiment (MSX) at LANL have enabled unprecedented access to the physical processes arising from stagnating magnetized (β ~ 1), collisionless, highly supersonic (M ,MA ~ 10) flows, similar in dimensionless parameters to those found in both space and astrophysical shocks. Hot (100s of eV during translation), dense (1022 - 1023 m-3) Field Reversed Configuration (FRC) plasmoids are accelerated to high velocities (100s of km/s) and subsequently impact against a static target such as a strong parallel or anti-parallel (reconnection-wise) magnetic mirror, a solid obstacle, or neutral gas cloud to recreate the physics of interest with characteristic length and time scales that are both large enough to observe yet small enough to fit within the experiment. Long-lived (>50 μs) stagnated plasmas with density enhancement much greater than predicted by fluid theory (>4x) are observed, accompanied by discontinuous plasma structures indicating shocks and jetting (visible emission and interferometry) and copious >1 keV x-ray emission. An overview of the experimental program will be presented, including machine design and capabilities, diagnostics, and an examination of the physical processes that occur during stagnation against a variety of targets. Supported by the DOE Office of Fusion Energy Sciences under contract DE-AC52-06NA25369.

Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances

PubMed Central

Mincholé, Ana; Martínez, Juan Pablo; Laguna, Pablo; Rodriguez, Blanca

2018-01-01

Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first step to help diagnose, understand and predict cardiovascular disorders responsible for 30% of deaths worldwide. Computational techniques, and more specifically machine learning techniques and computational modelling are powerful tools for classification, clustering and simulation, and they have recently been applied to address the analysis of medical data, especially ECG data. This review describes the computational methods in use for ECG analysis, with a focus on machine learning and 3D computer simulations, as well as their accuracy, clinical implications and contributions to medical advances. The first section focuses on heartbeat classification and the techniques developed to extract and classify abnormal from regular beats. The second section focuses on patient diagnosis from whole recordings, applied to different diseases. The third section presents real-time diagnosis and applications to wearable devices. The fourth section highlights the recent field of personalized ECG computer simulations and their interpretation. Finally, the discussion section outlines the challenges of ECG analysis and provides a critical assessment of the methods presented. The computational methods reported in this review are a strong asset for medical discoveries and their translation to the clinical world may lead to promising advances. PMID:29321268

Brain-machine interfaces: electrophysiological challenges and limitations.

PubMed

Lega, Bradley C; Serruya, Mijail D; Zaghloul, Kareem A

2011-01-01

Brain-machine interfaces (BMI) seek to directly communicate with the human nervous system in order to diagnose and treat intrinsic neurological disorders. While the first generation of these devices has realized significant clinical successes, they often rely on gross electrical stimulation using empirically derived parameters through open-loop mechanisms of action that are not yet fully understood. Their limitations reflect the inherent challenge in developing the next generation of these devices. This review identifies lessons learned from the first generation of BMI devices (chiefly deep brain stimulation), identifying key problems for which the solutions will aid the development of the next generation of technologies. Our analysis examines four hypotheses for the mechanism by which brain stimulation alters surrounding neurophysiologic activity. We then focus on motor prosthetics, describing various approaches to overcoming the problems of decoding neural signals. We next turn to visual prosthetics, an area for which the challenges of signal coding to match neural architecture has been partially overcome. Finally, we close with a review of cortical stimulation, examining basic principles that will be incorporated into the design of future devices. Throughout the review, we relate the issues of each specific topic to the common thread of BMI research: translating new knowledge of network neuroscience into improved devices for neuromodulation.

[Correction of respiratory movement using ultrasound for cardiac nuclear medicine examinations: fundamental study using an X-ray TV machine].

PubMed

Yoda, Kazushige; Umeda, Tokuo; Hasegawa, Tomoyuki

2003-11-01

Organ movements that occur naturally as a result of vital functions such as respiration and heartbeat cause deterioration of image quality in nuclear medicine imaging. Among these movements, respiration has a large effect, but there has been no practical method of correcting for this. In the present study, we examined a method of correction that uses ultrasound images to correct baseline shifts caused by respiration in cardiac nuclear medicine examinations. To evaluate the validity of this method, simulation studies were conducted with an X-ray TV machine instead of a nuclear medicine scanner. The X-ray TV images and ultrasound images were recorded as digital movies and processed with public domain software (Scion Image). Organ movements were detected in the ultrasound images of the subcostal four-chamber view mode using slit regions of interest and were measured on a two-dimensional image coordinate. Then translational shifts were applied to the X-ray TV images to correct these movements by using macro-functions of the software. As a result, respiratory movements of about 20.1 mm were successfully reduced to less than 2.6 mm. We conclude that this correction technique is potentially useful in nuclear medicine cardiology.

Prediction of human disease-associated phosphorylation sites with combined feature selection approach and support vector machine.

PubMed

Xu, Xiaoyi; Li, Ao; Wang, Minghui

2015-08-01

Phosphorylation is a crucial post-translational modification, which regulates almost all cellular processes in life. It has long been recognised that protein phosphorylation has close relationship with diseases, and therefore many researches are undertaken to predict phosphorylation sites for disease treatment and drug design. However, despite the success achieved by these approaches, no method focuses on disease-associated phosphorylation sites prediction. Herein, for the first time the authors propose a novel approach that is specially designed to identify associations between phosphorylation sites and human diseases. To take full advantage of local sequence information, a combined feature selection method-based support vector machine (CFS-SVM) that incorporates minimum-redundancy-maximum-relevance filtering process and forward feature selection process is developed. Performance evaluation shows that CFS-SVM is significantly better than the widely used classifiers including Bayesian decision theory, k nearest neighbour and random forest. With the extremely high specificity of 99%, CFS-SVM can still achieve a high sensitivity. Besides, tests on extra data confirm the effectiveness and general applicability of CFS-SVM approach on a variety of diseases. Finally, the analysis of selected features and corresponding kinases also help the understanding of the potential mechanism of disease-phosphorylation relationships and guide further experimental validations.

Prediction of brain maturity in infants using machine-learning algorithms.

PubMed

Smyser, Christopher D; Dosenbach, Nico U F; Smyser, Tara A; Snyder, Abraham Z; Rogers, Cynthia E; Inder, Terrie E; Schlaggar, Bradley L; Neil, Jeffrey J

2016-08-01

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical approaches can help translate the improved understanding of early functional connectivity provided through these studies into predictive models of neurodevelopmental outcome. One approach to achieving this goal is multivariate pattern analysis, a machine-learning, pattern classification approach well-suited for high-dimensional neuroimaging data. It has previously been adapted to predict brain maturity in children and adolescents using structural and resting state-functional MRI data. In this study, we evaluated resting state-functional MRI data from 50 preterm-born infants (born at 23-29weeks of gestation and without moderate-severe brain injury) scanned at term equivalent postmenstrual age compared with data from 50 term-born control infants studied within the first week of life. Using 214 regions of interest, binary support vector machines distinguished term from preterm infants with 84% accuracy (p<0.0001). Inter- and intra-hemispheric connections throughout the brain were important for group categorization, indicating that widespread changes in the brain's functional network architecture associated with preterm birth are detectable by term equivalent age. Support vector regression enabled quantitative estimation of birth gestational age in single subjects using only term equivalent resting state-functional MRI data, indicating that the present approach is sensitive to the degree of disruption of brain development associated with preterm birth (using gestational age as a surrogate for the extent of disruption). This suggests that support vector regression may provide a means for predicting neurodevelopmental outcome in individual infants. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction of brain maturity in infants using machine-learning algorithms

PubMed Central

Smyser, Christopher D.; Dosenbach, Nico U.F.; Smyser, Tara A.; Snyder, Abraham Z.; Rogers, Cynthia E.; Inder, Terrie E.; Schlaggar, Bradley L.; Neil, Jeffrey J.

2016-01-01

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical approaches can help translate the improved understanding of early functional connectivity provided through these studies into predictive models of neurodevelopmental outcome. One approach to achieving this goal is multivariate pattern analysis, a machine-learning, pattern classification approach well-suited for high-dimensional neuroimaging data. It has previously been adapted to predict brain maturity in children and adolescents using structural and resting state-functional MRI data. In this study, we evaluated resting state-functional MRI data from 50 preterm-born infants (born at 23–29 weeks of gestation and without moderate–severe brain injury) scanned at term equivalent postmenstrual age compared with data from 50 term-born control infants studied within the first week of life. Using 214 regions of interest, binary support vector machines distinguished term from preterm infants with 84% accuracy (p < 0.0001). Inter- and intra-hemispheric connections throughout the brain were important for group categorization, indicating that widespread changes in the brain's functional network architecture associated with preterm birth are detectable by term equivalent age. Support vector regression enabled quantitative estimation of birth gestational age in single subjects using only term equivalent resting state-functional MRI data, indicating that the present approach is sensitive to the degree of disruption of brain development associated with preterm birth (using gestational age as a surrogate for the extent of disruption). This suggests that support vector regression may provide a means for predicting neurodevelopmental outcome in individual infants. PMID:27179605

Direction of spin axis and spin rate of the pitched baseball.

PubMed

Jinji, Tsutomu; Sakurai, Shinji

2006-07-01

In this study, we aimed to determine the direction of the spin axis and the spin rate of pitched baseballs and to estimate the associated aerodynamic forces. In addition, the effects of the spin axis direction and spin rate on the trajectory of a pitched baseball were evaluated. The trajectories of baseballs pitched by both a pitcher and a pitching machine were recorded using four synchronized video cameras (60 Hz) and were analyzed using direct linear transform (DLT) procedures. A polynomial function using the least squares method was used to derive the time-displacement relationship of the ball coordinates during flight for each pitch. The baseball was filmed immediately after ball release using a high-speed video camera (250 Hz), and the direction of the spin axis and the spin rate (omega) were calculated based on the positional changes of the marks on the ball. The lift coefficient was correlated closely with omegasinalpha (r = 0.860), where alpha is the angle between the spin axis and the pitching direction. The term omegasinalpha represents the vertical component of the velocity vector. The lift force, which is a result of the Magnus effect occurring because of the rotation of the ball, acts perpendicularly to the axis of rotation. The Magnus effect was found to be greatest when the angular and translational velocity vectors were perpendicular to each other, and the break of the pitched baseball became smaller as the angle between these vectors approached 0 degrees. Balls delivered from a pitching machine broke more than actual pitcher's balls. It is necessary to consider the differences when we use pitching machines in batting practice.

A virtual simulator designed for collision prevention in proton therapy.

PubMed

Jung, Hyunuk; Kum, Oyeon; Han, Youngyih; Park, Hee Chul; Kim, Jin Sung; Choi, Doo Ho

2015-10-01

In proton therapy, collisions between the patient and nozzle potentially occur because of the large nozzle structure and efforts to minimize the air gap. Thus, software was developed to predict such collisions between the nozzle and patient using treatment virtual simulation. Three-dimensional (3D) modeling of a gantry inner-floor, nozzle, and robotic-couch was performed using SolidWorks based on the manufacturer's machine data. To obtain patient body information, a 3D-scanner was utilized right before CT scanning. Using the acquired images, a 3D-image of the patient's body contour was reconstructed. The accuracy of the image was confirmed against the CT image of a humanoid phantom. The machine components and the virtual patient were combined on the treatment-room coordinate system, resulting in a virtual simulator. The simulator simulated the motion of its components such as rotation and translation of the gantry, nozzle, and couch in real scale. A collision, if any, was examined both in static and dynamic modes. The static mode assessed collisions only at fixed positions of the machine's components, while the dynamic mode operated any time a component was in motion. A collision was identified if any voxels of two components, e.g., the nozzle and the patient or couch, overlapped when calculating volume locations. The event and collision point were visualized, and collision volumes were reported. All components were successfully assembled, and the motions were accurately controlled. The 3D-shape of the phantom agreed with CT images within a deviation of 2 mm. Collision situations were simulated within minutes, and the results were displayed and reported. The developed software will be useful in improving patient safety and clinical efficiency of proton therapy.

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.

Analysis and Prediction of Myristoylation Sites Using the mRMR Method, the IFS Method and an Extreme Learning Machine Algorithm.

PubMed

Wang, ShaoPeng; Zhang, Yu-Hang; Huang, GuoHua; Chen, Lei; Cai, Yu-Dong

2017-01-01

Myristoylation is an important hydrophobic post-translational modification that is covalently bound to the amino group of Gly residues on the N-terminus of proteins. The many diverse functions of myristoylation on proteins, such as membrane targeting, signal pathway regulation and apoptosis, are largely due to the lipid modification, whereas abnormal or irregular myristoylation on proteins can lead to several pathological changes in the cell. To better understand the function of myristoylated sites and to correctly identify them in protein sequences, this study conducted a novel computational investigation on identifying myristoylation sites in protein sequences. A training dataset with 196 positive and 84 negative peptide segments were obtained. Four types of features derived from the peptide segments following the myristoylation sites were used to specify myristoylatedand non-myristoylated sites. Then, feature selection methods including maximum relevance and minimum redundancy (mRMR), incremental feature selection (IFS), and a machine learning algorithm (extreme learning machine method) were adopted to extract optimal features for the algorithm to identify myristoylation sites in protein sequences, thereby building an optimal prediction model. As a result, 41 key features were extracted and used to build an optimal prediction model. The effectiveness of the optimal prediction model was further validated by its performance on a test dataset. Furthermore, detailed analyses were also performed on the extracted 41 features to gain insight into the mechanism of myristoylation modification. This study provided a new computational method for identifying myristoylation sites in protein sequences. We believe that it can be a useful tool to predict myristoylation sites from protein sequences. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Signal recognition particle assembly in relation to the function of amplified nucleoli of Xenopus oocytes.

PubMed

Sommerville, John; Brumwell, Craig L; Politz, Joan C Ritland; Pederson, Thoru

2005-03-15

The signal recognition particle (SRP) is a ribonucleoprotein machine that controls the translation and intracellular sorting of membrane and secreted proteins. The SRP contains a core RNA subunit with which six proteins are assembled. Recent work in both yeast and mammalian cells has identified the nucleolus as a possible initial site of SRP assembly. In the present study, SRP RNA and protein components were identified in the extrachromosomal, amplified nucleoli of Xenopus laevis oocytes. Fluorescent SRP RNA microinjected into the oocyte nucleus became specifically localized in the nucleoli, and endogenous SRP RNA was also detected in oocyte nucleoli by RNA in situ hybridization. An initial step in the assembly of SRP involves the binding of the SRP19 protein to SRP RNA. When green fluorescent protein (GFP)-tagged SRP19 protein was injected into the oocyte cytoplasm it was imported into the nucleus and became concentrated in the amplified nucleoli. After visiting the amplified nucleoli, GFP-tagged SRP19 protein was detected in the cytoplasm in a ribonucleoprotein complex, having a sedimentation coefficient characteristic of the SRP. These results suggest that the amplified nucleoli of Xenopus oocytes produce maternal stores not only of ribosomes, the classical product of nucleoli, but also of SRP, presumably as a global developmental strategy for stockpiling translational machinery for early embryogenesis.

Design Through Manufacturing: The Solid Model - Finite Element Analysis Interface

NASA Technical Reports Server (NTRS)

Rubin, Carol

2003-01-01

State-of-the-art computer aided design (CAD) presently affords engineers the opportunity to create solid models of machine parts which reflect every detail of the finished product. Ideally, these models should fulfill two very important functions: (1) they must provide numerical control information for automated manufacturing of precision parts, and (2) they must enable analysts to easily evaluate the stress levels (using finite element analysis - FEA) for all structurally significant parts used in space missions. Today's state-of-the-art CAD programs perform function (1) very well, providing an excellent model for precision manufacturing. But they do not provide a straightforward and simple means of automating the translation from CAD to FEA models, especially for aircraft-type structures. The research performed during the fellowship period investigated the transition process from the solid CAD model to the FEA stress analysis model with the final goal of creating an automatic interface between the two. During the period of the fellowship a detailed multi-year program for the development of such an interface was created. The ultimate goal of this program will be the development of a fully parameterized automatic ProE/FEA translator for parts and assemblies, with the incorporation of data base management into the solution, and ultimately including computational fluid dynamics and thermal modeling in the interface.

Evaluation of molecular brain changes associated with environmental stress in rodent models compared to human major depressive disorder: A proteomic systems approach.

PubMed

Cox, David Alan; Gottschalk, Michael Gerd; Stelzhammer, Viktoria; Wesseling, Hendrik; Cooper, Jason David; Bahn, Sabine

2016-11-25

Rodent models of major depressive disorder (MDD) are indispensable when screening for novel treatments, but assessing their translational relevance with human brain pathology has proved difficult. Using a novel systems approach, proteomics data obtained from post-mortem MDD anterior prefrontal cortex tissue (n = 12) and matched controls (n = 23) were compared with equivalent data from three commonly used preclinical models exposed to environmental stressors (chronic mild stress, prenatal stress and social defeat). Functional pathophysiological features associated with depression-like behaviour were identified in these models through enrichment of protein-protein interaction networks. A cross-species comparison evaluated which model(s) represent human MDD pathology most closely. Seven functional domains associated with MDD and represented across at least two models such as "carbohydrate metabolism and cellular respiration" were identified. Through statistical evaluation using kernel-based machine learning techniques, the social defeat model was found to represent MDD brain changes most closely for four of the seven domains. This is the first study to apply a method for directly evaluating the relevance of the molecular pathology of multiple animal models to human MDD on the functional level. The methodology and findings outlined here could help to overcome translational obstacles of preclinical psychiatric research.

A homology-based pipeline for global prediction of post-translational modification sites

NASA Astrophysics Data System (ADS)

Chen, Xiang; Shi, Shao-Ping; Xu, Hao-Dong; Suo, Sheng-Bao; Qiu, Jian-Ding

2016-05-01

The pathways of protein post-translational modifications (PTMs) have been shown to play particularly important roles for almost any biological process. Identification of PTM substrates along with information on the exact sites is fundamental for fully understanding or controlling biological processes. Alternative computational strategies would help to annotate PTMs in a high-throughput manner. Traditional algorithms are suited for identifying the common organisms and tissues that have a complete PTM atlas or extensive experimental data. While annotation of rare PTMs in most organisms is a clear challenge. In this work, to this end we have developed a novel homology-based pipeline named PTMProber that allows identification of potential modification sites for most of the proteomes lacking PTMs data. Cross-promotion E-value (CPE) as stringent benchmark has been used in our pipeline to evaluate homology to known modification sites. Independent-validation tests show that PTMProber achieves over 58.8% recall with high precision by CPE benchmark. Comparisons with other machine-learning tools show that PTMProber pipeline performs better on general predictions. In addition, we developed a web-based tool to integrate this pipeline at http://bioinfo.ncu.edu.cn/PTMProber/index.aspx. In addition to pre-constructed prediction models of PTM, the website provides an extensional functionality to allow users to customize models.

A one-piece 3D printed flexure translation stage for open-source microscopy

NASA Astrophysics Data System (ADS)

Sharkey, James P.; Foo, Darryl C. W.; Kabla, Alexandre; Baumberg, Jeremy J.; Bowman, Richard W.

2016-02-01

Open source hardware has the potential to revolutionise the way we build scientific instruments; with the advent of readily available 3D printers, mechanical designs can now be shared, improved, and replicated faster and more easily than ever before. However, printed parts are typically plastic and often perform poorly compared to traditionally machined mechanisms. We have overcome many of the limitations of 3D printed mechanisms by exploiting the compliance of the plastic to produce a monolithic 3D printed flexure translation stage, capable of sub-micron-scale motion over a range of 8 × 8 × 4 mm. This requires minimal post-print clean-up and can be automated with readily available stepper motors. The resulting plastic composite structure is very stiff and exhibits remarkably low drift, moving less than 20 μm over the course of a week, without temperature stabilisation. This enables us to construct a miniature microscope with excellent mechanical stability, perfect for time-lapse measurements in situ in an incubator or fume hood. The ease of manufacture lends itself to use in containment facilities where disposability is advantageous and to experiments requiring many microscopes in parallel. High performance mechanisms based on printed flexures need not be limited to microscopy, and we anticipate their use in other devices both within the laboratory and beyond.

CAD/CAM/AM applications in the manufacture of dental appliances.

PubMed

Al Mortadi, Noor; Eggbeer, Dominic; Lewis, Jeffrey; Williams, Robert J

2012-11-01

The purposes of this study were to apply the latest developments in additive manufacturing (AM) construction and to evaluate the effectiveness of these computer-aided design and computer-aided manufacturing (CAD/CAM) techniques in the production of dental appliances. In addition, a new method of incorporating wire into a single build was developed. A scanner was used to capture 3-dimensional images of Class II Division 1 dental models that were translated onto a 2-dimensional computer screen. Andresen and sleep-apnea devices were designed in 3 dimensions by using FreeForm software (version 11; Geo Magics SensAble Group, Wilmington, Mass) and a phantom arm. The design was then exported and transferred to an AM machine for building. Copyright © 2012 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Transverse vibration of Bernoulli Euler beams carrying point masses and taking into account their rotatory inertia: Exact solution

NASA Astrophysics Data System (ADS)

Maiz, Santiago; Bambill, Diana V.; Rossit, Carlos A.; Laura, P. A. A.

2007-06-01

The situation of structural elements supporting motors or engines attached to them is usual in technological applications. The operation of the machine may introduce severe dynamic stresses on the beam. It is important, then, to know the natural frequencies of the coupled beam-mass system, in order to obtain a proper design of the structural elements. An exact solution for the title problem is obtained in closed-form fashion, considering general boundary conditions by means of translational and rotatory springs at both ends. The model allows to analyze the influence of the masses and their rotatory inertia on the dynamic behavior of beams with all the classic boundary conditions, and also, as particular cases, to determine the frequencies of continuous beams.

A perspective on intelligent devices and environments in medical rehabilitation.

PubMed

Cooper, Rory A; Dicianno, Brad E; Brewer, Bambi; LoPresti, Edmund; Ding, Dan; Simpson, Richard; Grindle, Garrett; Wang, Hongwu

2008-12-01

Globally, the number of people older than 65 years is anticipated to double between 1997 and 2025, while at the same time the number of people with disabilities is growing at a similar rate, which makes technical advances and social policies critical to attain, prolong, and preserve quality of life. Recent advancements in technology, including computation, robotics, machine learning, communication, and miniaturization of sensors have been used primarily in manufacturing, military, space exploration, and entertainment. However, few efforts have been made to utilize these technologies to enhance the quality of life of people with disabilities. This article offers a perspective of future development in seven emerging areas: translation of research into clinical practice, pervasive assistive technology, cognitive assistive technologies, rehabilitation monitoring and coaching technologies, robotic assisted therapy, and personal mobility and manipulation technology.

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.

PubMed

Huggins, Jane E; Guger, Christoph; Allison, Brendan; Anderson, Charles W; Batista, Aaron; Brouwer, Anne-Marie A-M; Brunner, Clemens; Chavarriaga, Ricardo; Fried-Oken, Melanie; Gunduz, Aysegul; Gupta, Disha; Kübler, Andrea; Leeb, Robert; Lotte, Fabien; Miller, Lee E; Müller-Putz, Gernot; Rutkowski, Tomasz; Tangermann, Michael; Thompson, David Edward

2014-01-01

The Fifth International Brain-Computer Interface (BCI) Meeting met June 3-7 th , 2013 at the Asilomar Conference Grounds, Pacific Grove, California. The conference included 19 workshops covering topics in brain-computer interface and brain-machine interface research. Topics included translation of BCIs into clinical use, standardization and certification, types of brain activity to use for BCI, recording methods, the effects of plasticity, special interest topics in BCIs applications, and future BCI directions. BCI research is well established and transitioning to practical use to benefit people with physical impairments. At the same time, new applications are being explored, both for people with physical impairments and beyond. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and high-lighting important issues for future research and development.

How do the Polytechnic Students Cope with the Difficulties in Composing Abstracts for Their Final Projects?

NASA Astrophysics Data System (ADS)

Niswatin, C.; Latief, M. A.; Suharyadi, S.

2018-02-01

This research aims to uncover the fact about engineering students in dealing with composing abstracts for their final projects. The research applies a descriptive qualitative quantitative design. The data were collected through questioners involving 104 engineering students, including the alumni at Politeknik Kota Malang, Indonesia. Furthermore, interviews were carried out to explain the details where necessary to support the primary data. It is found that the common problems faced by engineering students include 1) combining words into sentences, 2) identifying the most appropriate technical terms in engineering, and 3) applying grammar in context. To cope with those difficulties they demanded translation application machines, supported by peer-proofreaders. In addition, they considerably engaged personal tutoring with the lectures more than three times.

Multidimensional Simulation Applied to Water Resources Management

NASA Astrophysics Data System (ADS)

Camara, A. S.; Ferreira, F. C.; Loucks, D. P.; Seixas, M. J.

1990-09-01

A framework for an integrated decision aiding simulation (IDEAS) methodology using numerical, linguistic, and pictorial entities and operations is introduced. IDEAS relies upon traditional numerical formulations, logical rules to handle linguistic entities with linguistic values, and a set of pictorial operations. Pictorial entities are defined by their shape, size, color, and position. Pictorial operators include reproduction (copy of a pictorial entity), mutation (expansion, rotation, translation, change in color), fertile encounters (intersection, reunion), and sterile encounters (absorption). Interaction between numerical, linguistic, and pictorial entities is handled through logical rules or a simplified vector calculus operation. This approach is shown to be applicable to various environmental and water resources management analyses using a model to assess the impacts of an oil spill. Future developments, including IDEAS implementation on parallel processing machines, are also discussed.

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.

An image registration based ultrasound probe calibration

NASA Astrophysics Data System (ADS)

Li, Xin; Kumar, Dinesh; Sarkar, Saradwata; Narayanan, Ram

2012-02-01

Reconstructed 3D ultrasound of prostate gland finds application in several medical areas such as image guided biopsy, therapy planning and dose delivery. In our application, we use an end-fire probe rotated about its axis to acquire a sequence of rotational slices to reconstruct 3D TRUS (Transrectal Ultrasound) image. The image acquisition system consists of an ultrasound transducer situated on a cradle directly attached to a rotational sensor. However, due to system tolerances, axis of probe does not align exactly with the designed axis of rotation resulting in artifacts in the 3D reconstructed ultrasound volume. We present a rigid registration based automatic probe calibration approach. The method uses a sequence of phantom images, each pair acquired at angular separation of 180 degrees and registers corresponding image pairs to compute the deviation from designed axis. A modified shadow removal algorithm is applied for preprocessing. An attribute vector is constructed from image intensity and a speckle-insensitive information-theoretic feature. We compare registration between the presented method and expert-corrected images in 16 prostate phantom scans. Images were acquired at multiple resolutions, and different misalignment settings from two ultrasound machines. Screenshots from 3D reconstruction are shown before and after misalignment correction. Registration parameters from automatic and manual correction were found to be in good agreement. Average absolute differences of translation and rotation between automatic and manual methods were 0.27 mm and 0.65 degree, respectively. The registration parameters also showed lower variability for automatic registration (pooled standard deviation σtranslation = 0.50 mm, σrotation = 0.52 degree) compared to the manual approach (pooled standard deviation σtranslation = 0.62 mm, σrotation = 0.78 degree).

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.

A rabbit model of cerebral microembolic signals for translational research: preclinical validation for aspirin and clopidogrel.

PubMed

Zhou, X; Kurowski, S; Wu, W; Desai, K; Chu, L; Gutstein, D E; Seiffert, D; Wang, X

2016-09-01

Essentials Microembolic signal (MES) is an independent predictor of stroke risk in patients. A rabbit model of cerebral microembolic signals was established. Therapeutic efficacy was demonstrated for aspirin and clopidogrel on microembolic signals. Potential translational value of this preclinical model of MES was demonstrated. Objectives Cerebral microembolic signals (MESs) detected by transcranial Doppler (TCD) ultrasound constitute an independent predictor of stroke risk and prognosis. The aim of this study was to develop a novel preclinical model of MESs to facilitate translational research. Methods A clinical TCD ultrasound machine was used to detect MESs in the cerebral circulation of New Zealand White rabbits. Technical feasibility was assessed for the measurement of MESs in the middle cerebral artery (MCA) by TCD. FeCl3 -induced carotid arterial thrombosis was optimized for the generation of endogenous microemboli. Ascending doses of two antithrombotic agents (aspirin and clopidogrel) were evaluated individually and in combination for their effects on both arterial thrombosis and MESs in a 30% FeCl3 -induced carotid arterial thrombosis model, along with ex vivo functional assays. Results Dose-dependent FeCl3 -induced arterial thrombosis studies showed that 30% FeCl3 resulted in the most consistent and reproducible MESs in the MCA (3.3 ± 0.7 MESs h(-1) ). Ascending-dose studies showed that the effective doses for 50% inhibition (ED50 ) of thrombus formation, based on integrated blood flow and thrombus weight, respectively, were 3.1 mg kg(-1) and 4.2 mg kg(-1) orally for aspirin, and 0.3 mg kg(-1) and 0.28 mg kg(-1) orally for clopidogrel. The ED50 values for MES incidence were 12.7 mg kg(-1) orally for aspirin, and 0.25 mg kg(-1) orally for clopidogrel. Dual treatment with aspirin (5 mg kg(-1) ) and clopidogel (0.3 mg kg(-1) ) resulted in significant reductions in cerebral MESs (P < 0.05) as compared with monotherapy with either agent. Conclusions Our study demonstrated the successful establishment of the MES model in rabbits, and it may provide translational value for MESs and ischemic stroke research. © 2016 International Society on Thrombosis and Haemostasis.

Mechanical properties of composite materials

NASA Technical Reports Server (NTRS)

Thornton, H. Richard; Cornwell, L. R.

1993-01-01

A composite material incorporates high strength, high modulus fibers in a matrix (polymer, metal, or ceramic). The fibers may be oriented in a manner to give varying in-plane properties (longitudinal, transverse-stress, strain, and modulus of elasticity). The lay-up of the composite laminates is such that a center line of symmetry and no bending moment exist through the thickness. The laminates are tabbed, with either aluminum or fiberglass, and are ready for tensile testing. The determination of the tensile properties of resin matrix composites, reinforced by continuous fibers, is outlined in ASTM standard D 3039, Tensile Properties of Oriented Fiber Composites. The tabbed flat tensile coupons are placed into the grips of a tensile machine and load-deformation curves plotted. The load-deformation data are translated into stress-strain curves for determination of mechanical properties (ultimate tensile strength and modulus of elasticity).

VLSI-based video event triggering for image data compression

NASA Astrophysics Data System (ADS)

Williams, Glenn L.

1994-02-01

Long-duration, on-orbit microgravity experiments require a combination of high resolution and high frame rate video data acquisition. The digitized high-rate video stream presents a difficult data storage problem. Data produced at rates of several hundred million bytes per second may require a total mission video data storage requirement exceeding one terabyte. A NASA-designed, VLSI-based, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term (DC-like) or short term (AC-like) changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pre-trigger and post-trigger storage techniques are then adaptable to archiving only the significant video images.

Ceramic material life prediction: A program to translate ANSYS results to CARES/LIFE reliability analysis

NASA Technical Reports Server (NTRS)

Vonhermann, Pieter; Pintz, Adam

1994-01-01

This manual describes the use of the ANSCARES program to prepare a neutral file of FEM stress results taken from ANSYS Release 5.0, in the format needed by CARES/LIFE ceramics reliability program. It is intended for use by experienced users of ANSYS and CARES. Knowledge of compiling and linking FORTRAN programs is also required. Maximum use is made of existing routines (from other CARES interface programs and ANSYS routines) to extract the finite element results and prepare the neutral file for input to the reliability analysis. FORTRAN and machine language routines as described are used to read the ANSYS results file. Sub-element stresses are computed and written to a neutral file using FORTRAN subroutines which are nearly identical to those used in the NASCARES (MSC/NASTRAN to CARES) interface.

Design Through Manufacturing: The Solid Model-Finite Element Analysis Interface

NASA Technical Reports Server (NTRS)

Rubin, Carol

2002-01-01

State-of-the-art computer aided design (CAD) presently affords engineers the opportunity to create solid models of machine parts reflecting every detail of the finished product. Ideally, in the aerospace industry, these models should fulfill two very important functions: (1) provide numerical. control information for automated manufacturing of precision parts, and (2) enable analysts to easily evaluate the stress levels (using finite element analysis - FEA) for all structurally significant parts used in aircraft and space vehicles. Today's state-of-the-art CAD programs perform function (1) very well, providing an excellent model for precision manufacturing. But they do not provide a straightforward and simple means of automating the translation from CAD to FEA models, especially for aircraft-type structures. Presently, the process of preparing CAD models for FEA consumes a great deal of the analyst's time.

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future

PubMed Central

Huggins, Jane E.; Guger, Christoph; Allison, Brendan; Anderson, Charles W.; Batista, Aaron; Brouwer, Anne-Marie (A.-M.); Brunner, Clemens; Chavarriaga, Ricardo; Fried-Oken, Melanie; Gunduz, Aysegul; Gupta, Disha; Kübler, Andrea; Leeb, Robert; Lotte, Fabien; Miller, Lee E.; Müller-Putz, Gernot; Rutkowski, Tomasz; Tangermann, Michael; Thompson, David Edward

2014-01-01

The Fifth International Brain-Computer Interface (BCI) Meeting met June 3–7th, 2013 at the Asilomar Conference Grounds, Pacific Grove, California. The conference included 19 workshops covering topics in brain-computer interface and brain-machine interface research. Topics included translation of BCIs into clinical use, standardization and certification, types of brain activity to use for BCI, recording methods, the effects of plasticity, special interest topics in BCIs applications, and future BCI directions. BCI research is well established and transitioning to practical use to benefit people with physical impairments. At the same time, new applications are being explored, both for people with physical impairments and beyond. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and high-lighting important issues for future research and development. PMID:25485284

Rapid bespoke laser ablation of variable period grating structures using a digital micromirror device for multi-colored surface images.

PubMed

Heath, Daniel J; Mills, Ben; Feinaeugle, Matthias; Eason, Robert W

2015-06-01

A digital micromirror device has been used to project variable-period grating patterns at high values of demagnification for direct laser ablation on planar surfaces. Femtosecond laser pulses of ∼1  mJ pulse energy at 800 nm wavelength from a Ti:sapphire laser were used to machine complex patterns with areas of up to ∼1  cm² on thin films of bismuth telluride by dynamically modifying the grating period as the sample was translated beneath the imaged laser pulses. Individual ∼30 by 30 μm gratings were stitched together to form contiguous structures, which had diffractive effects clearly visible to the naked eye. This technique may have applications in marking, coding, and security features.

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

VLSI-based Video Event Triggering for Image Data Compression

NASA Technical Reports Server (NTRS)

Williams, Glenn L.

1994-01-01

Long-duration, on-orbit microgravity experiments require a combination of high resolution and high frame rate video data acquisition. The digitized high-rate video stream presents a difficult data storage problem. Data produced at rates of several hundred million bytes per second may require a total mission video data storage requirement exceeding one terabyte. A NASA-designed, VLSI-based, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term (DC-like) or short term (AC-like) changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pre-trigger and post-trigger storage techniques are then adaptable to archiving only the significant video images.

An improved method for identification of small non-coding RNAs in bacteria using support vector machine

NASA Astrophysics Data System (ADS)

Barman, Ranjan Kumar; Mukhopadhyay, Anirban; Das, Santasabuj

2017-04-01

Bacterial small non-coding RNAs (sRNAs) are not translated into proteins, but act as functional RNAs. They are involved in diverse biological processes like virulence, stress response and quorum sensing. Several high-throughput techniques have enabled identification of sRNAs in bacteria, but experimental detection remains a challenge and grossly incomplete for most species. Thus, there is a need to develop computational tools to predict bacterial sRNAs. Here, we propose a computational method to identify sRNAs in bacteria using support vector machine (SVM) classifier. The primary sequence and secondary structure features of experimentally-validated sRNAs of Salmonella Typhimurium LT2 (SLT2) was used to build the optimal SVM model. We found that a tri-nucleotide composition feature of sRNAs achieved an accuracy of 88.35% for SLT2. We validated the SVM model also on the experimentally-detected sRNAs of E. coli and Salmonella Typhi. The proposed model had robustly attained an accuracy of 81.25% and 88.82% for E. coli K-12 and S. Typhi Ty2, respectively. We confirmed that this method significantly improved the identification of sRNAs in bacteria. Furthermore, we used a sliding window-based method and identified sRNAs from complete genomes of SLT2, S. Typhi Ty2 and E. coli K-12 with sensitivities of 89.09%, 83.33% and 67.39%, respectively.

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

PubMed

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

2017-07-01

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

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.

Machine learning-based patient specific prompt-gamma dose monitoring in proton therapy

NASA Astrophysics Data System (ADS)

Gueth, P.; Dauvergne, D.; Freud, N.; Létang, J. M.; Ray, C.; Testa, E.; Sarrut, D.

2013-07-01

Online dose monitoring in proton therapy is currently being investigated with prompt-gamma (PG) devices. PG emission was shown to be correlated with dose deposition. This relationship is mostly unknown under real conditions. We propose a machine learning approach based on simulations to create optimized treatment-specific classifiers that detect discrepancies between planned and delivered dose. Simulations were performed with the Monte-Carlo platform Gate/Geant4 for a spot-scanning proton therapy treatment and a PG camera prototype currently under investigation. The method first builds a learning set of perturbed situations corresponding to a range of patient translation. This set is then used to train a combined classifier using distal falloff and registered correlation measures. Classifier performances were evaluated using receiver operating characteristic curves and maximum associated specificity and sensitivity. A leave-one-out study showed that it is possible to detect discrepancies of 5 mm with specificity and sensitivity of 85% whereas using only distal falloff decreases the sensitivity down to 77% on the same data set. The proposed method could help to evaluate performance and to optimize the design of PG monitoring devices. It is generic: other learning sets of deviations, other measures and other types of classifiers could be studied to potentially reach better performance. At the moment, the main limitation lies in the computation time needed to perform the simulations.

Neuron-Type-Specific Utility in a Brain-Machine Interface: a Pilot Study.

PubMed

Garcia-Garcia, Martha G; Bergquist, Austin J; Vargas-Perez, Hector; Nagai, Mary K; Zariffa, Jose; Marquez-Chin, Cesar; Popovic, Milos R

2017-11-01

Firing rates of single cortical neurons can be volitionally modulated through biofeedback (i.e. operant conditioning), and this information can be transformed to control external devices (i.e. brain-machine interfaces; BMIs). However, not all neurons respond to operant conditioning in BMI implementation. Establishing criteria that predict neuron utility will assist translation of BMI research to clinical applications. Single cortical neurons (n=7) were recorded extracellularly from primary motor cortex of a Long-Evans rat. Recordings were incorporated into a BMI involving up-regulation of firing rate to control the brightness of a light-emitting-diode and subsequent reward. Neurons were classified as 'fast-spiking', 'bursting' or 'regular-spiking' according to waveform-width and intrinsic firing patterns. Fast-spiking and bursting neurons were found to up-regulate firing rate by a factor of 2.43±1.16, demonstrating high utility, while regular-spiking neurons decreased firing rates on average by a factor of 0.73±0.23, demonstrating low utility. The ability to select neurons with high utility will be important to minimize training times and maximize information yield in future clinical BMI applications. The highly contrasting utility observed between fast-spiking and bursting neurons versus regular-spiking neurons allows for the hypothesis to be advanced that intrinsic electrophysiological properties may be useful criteria that predict neuron utility in BMI implementation.

Design and Manufacture of Elastically Tailored Tow Placed Plates

NASA Technical Reports Server (NTRS)

Tatting, Brain F.; Guerdal, Zafer; Jegley, Dawn (Technical Monitor)

2002-01-01

Elastic stiffness tailoring of laminated composite panels by allowing the fibers to curve within the plane of the laminate is a relatively novel design concept that has been demonstrated to be both beneficial and practical. In particular, for structures with highly non-uniform stress states, such as the case of a flat panel with a central hole subjected to in-plane loading, the concept is likely to provide substantial improvements in load carrying capability. The objective of the present study is to determine the effectiveness of stiffness tailoring through the use of curvilinear fibers to reduce stress concentrations around the hole and improve the load carrying capability of panels with holes. In this study software was created that translates standard finite element models with traditional laminate definitions into ones that possess stacking sequences with curvilinear fiber paths that are directly manufacturable using an advanced tow placement machine. Preliminary designs for the manufacturing and testing phase were determined through rudimentary design studies for flat plates without holes under axial compression. These candidate designs were then analyzed using finite element models that accurately reflect the test conditions and geometries in order to select final designs for testing. A total of six large panels, measuring three feet by six feet, each of which are used to produce four specimens with or without holes, were fabricated and delivered to NASA for machining and testing.

Controlled propulsion and separation of helical particles at the nanoscale.

PubMed

Alcanzare, Maria Michiko T; Thakore, Vaibhav; Ollila, Santtu T T; Karttunen, Mikko; Ala-Nissila, Tapio

2017-03-15

Controlling the motion of nano and microscale objects in a fluid environment is a key factor in designing optimized tiny machines that perform mechanical tasks such as transport of drugs or genetic material in cells, fluid mixing to accelerate chemical reactions, and cargo transport in microfluidic chips. Directed motion is made possible by the coupled translational and rotational motion of asymmetric particles. A current challenge in achieving directed and controlled motion at the nanoscale lies in overcoming random Brownian motion due to thermal fluctuations in the fluid. We use a hybrid lattice-Boltzmann molecular dynamics method with full hydrodynamic interactions and thermal fluctuations to demonstrate that controlled propulsion of individual nanohelices in an aqueous environment is possible. We optimize the propulsion velocity and the efficiency of externally driven nanohelices. We quantify the importance of the thermal effects on the directed motion by calculating the Péclet number for various shapes, number of turns and pitch lengths of the helices. Consistent with the experimental microscale separation of chiral objects, our results indicate that in the presence of thermal fluctuations at Péclet numbers >10, chiral particles follow the direction of propagation according to its handedness and the direction of the applied torque making separation of chiral particles possible at the nanoscale. Our results provide criteria for the design and control of helical machines at the nanoscale.

Brain-machine interfaces in neurorehabilitation of stroke.

PubMed

Soekadar, Surjo R; Birbaumer, Niels; Slutzky, Marc W; Cohen, Leonardo G

2015-11-01

Stroke is among the leading causes of long-term disabilities leaving an increasing number of people with cognitive, affective and motor impairments depending on assistance in their daily life. While function after stroke can significantly improve in the first weeks and months, further recovery is often slow or non-existent in the more severe cases encompassing 30-50% of all stroke victims. The neurobiological mechanisms underlying recovery in those patients are incompletely understood. However, recent studies demonstrated the brain's remarkable capacity for functional and structural plasticity and recovery even in severe chronic stroke. As all established rehabilitation strategies require some remaining motor function, there is currently no standardized and accepted treatment for patients with complete chronic muscle paralysis. The development of brain-machine interfaces (BMIs) that translate brain activity into control signals of computers or external devices provides two new strategies to overcome stroke-related motor paralysis. First, BMIs can establish continuous high-dimensional brain-control of robotic devices or functional electric stimulation (FES) to assist in daily life activities (assistive BMI). Second, BMIs could facilitate neuroplasticity, thus enhancing motor learning and motor recovery (rehabilitative BMI). Advances in sensor technology, development of non-invasive and implantable wireless BMI-systems and their combination with brain stimulation, along with evidence for BMI systems' clinical efficacy suggest that BMI-related strategies will play an increasing role in neurorehabilitation of stroke. Copyright © 2014. Published by Elsevier Inc.

Identifying N6-methyladenosine sites using multi-interval nucleotide pair position specificity and support vector machine

NASA Astrophysics Data System (ADS)

Xing, Pengwei; Su, Ran; Guo, Fei; Wei, Leyi

2017-04-01

N6-methyladenosine (m6A) refers to methylation of the adenosine nucleotide acid at the nitrogen-6 position. It plays an important role in a series of biological processes, such as splicing events, mRNA exporting, nascent mRNA synthesis, nuclear translocation and translation process. Numerous experiments have been done to successfully characterize m6A sites within sequences since high-resolution mapping of m6A sites was established. However, as the explosive growth of genomic sequences, using experimental methods to identify m6A sites are time-consuming and expensive. Thus, it is highly desirable to develop fast and accurate computational identification methods. In this study, we propose a sequence-based predictor called RAM-NPPS for identifying m6A sites within RNA sequences, in which we present a novel feature representation algorithm based on multi-interval nucleotide pair position specificity, and use support vector machine classifier to construct the prediction model. Comparison results show that our proposed method outperforms the state-of-the-art predictors on three benchmark datasets across the three species, indicating the effectiveness and robustness of our method. Moreover, an online webserver implementing the proposed predictor has been established at http://server.malab.cn/RAM-NPPS/. It is anticipated to be a useful prediction tool to assist biologists to reveal the mechanisms of m6A site functions.

The strategic offense initiative? The Soviets and Star Wars

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

Westwick, Peter J.

2014-05-09

Historians of the Cold War have paid too little attention to Soviet fears of 'space-strike weapons' - that is, possible offensive uses of President Ronald Reagan's Strategic Defense Initiative. In fifteen years or so, soldiers will no longer shoot rifles but will use some kind of lightning, some sort of a machine emitting a holocaustal electrical beam. Tell me, what can we invent in this line so as to surprise our neighbors?... Alas, we are only capable of imitating and purchasing weapons from others, and we do well if we manage to repair them ourselves. --Fyodor Dostoevsky, A Writer's Diary,more » 1873. [Khlinov, a physicist]: 'I know that he has made an important discovery concerning the transmission of infra-red rays over a distance.... Heat waves at a temperature of a thousand degrees centigrade transmitted parallel to each other constitute a monstrous weapon of destruction and defense in time of war. The whole secret lies in the transmission of a ray that does not disperse. So far nobody has been able to do this. Judging by your story, Garin has constructed a machine that will do it. If so it is an extremely important discovery.' 'I've been thinking for a long time that this invention smells of higher politics,' said Shelga. --Aleksei Tolstoy, The Garin Death Ray, 1927 (translated by George Hanna)« less

Precision Oncology beyond Targeted Therapy: Combining Omics Data with Machine Learning Matches the Majority of Cancer Cells to Effective Therapeutics.

PubMed

Ding, Michael Q; Chen, Lujia; Cooper, Gregory F; Young, Jonathan D; Lu, Xinghua

2018-02-01

Precision oncology involves identifying drugs that will effectively treat a tumor and then prescribing an optimal clinical treatment regimen. However, most first-line chemotherapy drugs do not have biomarkers to guide their application. For molecularly targeted drugs, using the genomic status of a drug target as a therapeutic indicator has limitations. In this study, machine learning methods (e.g., deep learning) were used to identify informative features from genome-scale omics data and to train classifiers for predicting the effectiveness of drugs in cancer cell lines. The methodology introduced here can accurately predict the efficacy of drugs, regardless of whether they are molecularly targeted or nonspecific chemotherapy drugs. This approach, on a per-drug basis, can identify sensitive cancer cells with an average sensitivity of 0.82 and specificity of 0.82; on a per-cell line basis, it can identify effective drugs with an average sensitivity of 0.80 and specificity of 0.82. This report describes a data-driven precision medicine approach that is not only generalizable but also optimizes therapeutic efficacy. The framework detailed herein, when successfully translated to clinical environments, could significantly broaden the scope of precision oncology beyond targeted therapies, benefiting an expanded proportion of cancer patients. Mol Cancer Res; 16(2); 269-78. ©2017 AACR . ©2017 American Association for Cancer Research.

Exploring stakeholder perceptions of acceptability and feasibility of needle exchange programmes, syringe vending machines and safer injection facilities in Tijuana, Mexico.

PubMed

Philbin, Morgan M; Mantsios, Andrea; Lozada, Remedios; Case, Patricia; Pollini, Robin A; Alvelais, Jorge; Latkin, Carl A; Magis-Rodriguez, Carlos; Strathdee, Steffanie A

2009-07-01

Injection drug use is a growing public health crisis along the U.S.-Mexican border and rising rates of blood-borne infections highlight the pressing need for harm reduction interventions. We explored the acceptability and feasibility of such interventions in Tijuana, a city adjacent to San Diego, California. Using in-depth qualitative interviews conducted from August 2006-March 2007 with 40 key stakeholders - pharmacists, legal professionals, health officials, religious officials, drug treatment providers, and law enforcement personnel - we explored the acceptability and feasibility of interventions to reduce drug-related harm in Tijuana, Mexico. Interviews were taped with consent, transcribed verbatim, and translated. Content analysis was conducted to identify themes which included barriers, structural limitations, and suggestions for implementation. Topics included acceptance and feasibility of needle exchange programmes (NEPs), syringe vending machines, and safer injection facilities (SIFs), structural barriers and suggestions for implementation. Of these interventions, NEPs were deemed the most acceptable (75%); however, only half believed these could be feasibly implemented, citing barriers involving religion, police, and lack of political will, public awareness, and funding. Increasing HIV infection rates among injection drug users in Tijuana have prompted interest in public health responses. Our results may assist policy strategists in implementing social-structural interventions that will help create enabling environments that facilitate the scale-up and implementation of harm reduction in Tijuana.

A Python Analytical Pipeline to Identify Prohormone Precursors and Predict Prohormone Cleavage Sites

PubMed Central

Southey, Bruce R.; Sweedler, Jonathan V.; Rodriguez-Zas, Sandra L.

2008-01-01

Neuropeptides and hormones are signaling molecules that support cell–cell communication in the central nervous system. Experimentally characterizing neuropeptides requires significant efforts because of the complex and variable processing of prohormone precursor proteins into neuropeptides and hormones. We demonstrate the power and flexibility of the Python language to develop components of an bioinformatic analytical pipeline to identify precursors from genomic data and to predict cleavage as these precursors are en route to the final bioactive peptides. We identified 75 precursors in the rhesus genome, predicted cleavage sites using support vector machines and compared the rhesus predictions to putative assignments based on homology to human sequences. The correct classification rate of cleavage using the support vector machines was over 97% for both human and rhesus data sets. The functionality of Python has been important to develop and maintain NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html), a user-centered web application for the neuroscience community that provides cleavage site prediction from a wide range of models, precision and accuracy statistics, post-translational modifications, and the molecular mass of potential peptides. The combined results illustrate the suitability of the Python language to implement an all-inclusive bioinformatics approach to predict neuropeptides that encompasses a large number of interdependent steps, from scanning genomes for precursor genes to identification of potential bioactive neuropeptides. PMID:19169350

Kernelized rank learning for personalized drug recommendation.

PubMed

He, Xiao; Folkman, Lukas; Borgwardt, Karsten

2018-03-08

Large-scale screenings of cancer cell lines with detailed molecular profiles against libraries of pharmacological compounds are currently being performed in order to gain a better understanding of the genetic component of drug response and to enhance our ability to recommend therapies given a patient's molecular profile. These comprehensive screens differ from the clinical setting in which (1) medical records only contain the response of a patient to very few drugs, (2) drugs are recommended by doctors based on their expert judgment, and (3) selecting the most promising therapy is often more important than accurately predicting the sensitivity to all potential drugs. Current regression models for drug sensitivity prediction fail to account for these three properties. We present a machine learning approach, named Kernelized Rank Learning (KRL), that ranks drugs based on their predicted effect per cell line (patient), circumventing the difficult problem of precisely predicting the sensitivity to the given drug. Our approach outperforms several state-of-the-art predictors in drug recommendation, particularly if the training dataset is sparse, and generalizes to patient data. Our work phrases personalized drug recommendation as a new type of machine learning problem with translational potential to the clinic. The Python implementation of KRL and scripts for running our experiments are available at https://github.com/BorgwardtLab/Kernelized-Rank-Learning. xiao.he@bsse.ethz.ch, lukas.folkman@bsse.ethz.ch. Supplementary data are available at Bioinformatics online.

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.

Compliance analysis of a 3-DOF spindle head by considering gravitational effects

NASA Astrophysics Data System (ADS)

Li, Qi; Wang, Manxin; Huang, Tian; Chetwynd, Derek G.

2015-01-01

The compliance modeling is one of the most significant issues in the stage of preliminary design for parallel kinematic machine(PKM). The gravity ignored in traditional compliance analysis has a significant effect on pose accuracy of tool center point(TCP) when a PKM is horizontally placed. By taking gravity into account, this paper presents a semi-analytical approach for compliance analysis of a 3-DOF spindle head named the A3 head. The architecture behind the A3 head is a 3-R PS parallel mechanism having one translational and two rotational movement capabilities, which can be employed to form the main body of a 5-DOF hybrid kinematic machine especially designed for high-speed machining of large aircraft components. The force analysis is carried out by considering both the externally applied wrench imposed upon the platform as well as gravity of all moving components. Then, the deflection analysis is investigated to establish the relationship between the deflection twist and compliances of all joints and links using semi-analytical method. The merits of this approach lie in that platform deflection twist throughout the entire task workspace can be evaluated in a very efficient manner. The effectiveness of the proposed approach is verified by the FEA and experiment at different configurations and the results show that the discrepancy of the compliances is less than 0.04 μm/N-1 and that of the deformations is less than 10μm. The computational and experimental results show that the deflection twist induced by gravity forces of the moving components has significant bearings on pose accuracy of the platform, providing an informative guidance for the improvement of the current design. The proposed approach can be easily applied to the compliance analysis of PKM by considering gravitational effects and to evaluate the deformation caused by gravity throughout the entire workspace.

Extending the coverage of the internet of things with low-cost nanosatellite networks

NASA Astrophysics Data System (ADS)

Almonacid, Vicente; Franck, Laurent

2017-09-01

Recent technology advances have made CubeSats not only an affordable means of access to space, but also promising platforms to develop a new variety of space applications. In this paper, we explore the idea of using nanosatellites as access points to provide extended coverage to the Internet of Things (IoT) and Machine-to-Machine (M2M) communications. This study is mainly motivated by two facts: on the one hand, it is already obvious that the number of machine-type devices deployed globally will experiment an exponential growth over the forthcoming years. This trend is pushed by the available terrestrial cellular infrastructure, which allows adding support for M2M connectivity at marginal costs. On the other hand, the same growth is not observed in remote areas that must rely on space-based connectivity. In such environments, the demand for M2M communications is potentially large, yet it is challenged by the lack of cost-effective service providers. The traffic characteristics of typical M2M applications translate into the requirement for an extremely low cost per transmitted message. Under these strong economical constraints, we expect that nanosatellites in the low Earth orbit will play a fundamental role in overcoming what we may call the IoT digital divide. The objective of this paper is therefore to provide a general analysis of a nanosatellite-based, global IoT/M2M network. We put emphasis in the engineering challenges faced in designing the Earth-to-Space communication link, where the adoption of an efficient multiple-access scheme is paramount for ensuring connectivity to a large number of terminal nodes. In particular, the trade-offs energy efficiency-access delay and energy efficiency-throughput are discussed, and a novel access approach suitable for delay-tolerant applications is proposed. Thus, by keeping a system-level standpoint, we identify key issues and discuss perspectives towards energy efficient and cost-effective solutions.

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

Gaballa, H; O’Brien, M; Riegel, A

Purpose: To develop a daily quality assurance (QA) device that can test the 6DoF (degrees of freedom) couch repositioning accuracy, prior to SBRT treatment deliveries, with an accuracy of ±0.3 degrees and ±0.3 mm. Methods: A daily QA phantom is designed with a focus on the derived center of projections of its markers, rather than tracking its individual markers one at a time. This approach can be the most favorable to address the intended machining accuracy of the QA phantom and the CBCT spatial resolution limitations, primarily 1 mm min slice thickness, simultaneously. With the current design, ±0.1 mm congruencemore » of the resultant center of gravity of the markers with reference CT (0.6 mm minimum slice thickness) vs CBCT (1.0 mm minimum slice thickness) can be achieved. If successful, the QA device should be qualified to test 6DoF couch performance with a gauged accuracy of ±0.3 degrees/±0.3 mm. Testing is performed for the Varian True Beam 2.0 6DoF system. Results: Once the QA phantom is constructed and tested, agreement of the center of gravity of the reference CT scan and the CBCT scan of ±0.1 mm is achieved. This has translated into a consistent 3D-3D match on the treatment machine, CT vs CBCT, with a repetitive ±0.1 mm variation, thus exceeding our expectations. We have deployed the phantom for daily QA on one of our accelerators, and found that the QA time has increased by only 10 minutes. Conclusion: A 6DoF phantom has been designed (patent pending) and built with a realistic work flow in mind where the daily couch accuracy QA checks taking less than 10 minutes. Current developments include integration with the Varian’s Machine Performance Check consistency module.« less

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

Multispectral imaging burn wound tissue classification system: a comparison of test accuracies between several common machine learning algorithms

NASA Astrophysics Data System (ADS)

Squiers, John J.; Li, Weizhi; King, Darlene R.; Mo, Weirong; Zhang, Xu; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

2016-03-01

The clinical judgment of expert burn surgeons is currently the standard on which diagnostic and therapeutic decisionmaking regarding burn injuries is based. Multispectral imaging (MSI) has the potential to increase the accuracy of burn depth assessment and the intraoperative identification of viable wound bed during surgical debridement of burn injuries. A highly accurate classification model must be developed using machine-learning techniques in order to translate MSI data into clinically-relevant information. An animal burn model was developed to build an MSI training database and to study the burn tissue classification ability of several models trained via common machine-learning algorithms. The algorithms tested, from least to most complex, were: K-nearest neighbors (KNN), decision tree (DT), linear discriminant analysis (LDA), weighted linear discriminant analysis (W-LDA), quadratic discriminant analysis (QDA), ensemble linear discriminant analysis (EN-LDA), ensemble K-nearest neighbors (EN-KNN), and ensemble decision tree (EN-DT). After the ground-truth database of six tissue types (healthy skin, wound bed, blood, hyperemia, partial injury, full injury) was generated by histopathological analysis, we used 10-fold cross validation to compare the algorithms' performances based on their accuracies in classifying data against the ground truth, and each algorithm was tested 100 times. The mean test accuracy of the algorithms were KNN 68.3%, DT 61.5%, LDA 70.5%, W-LDA 68.1%, QDA 68.9%, EN-LDA 56.8%, EN-KNN 49.7%, and EN-DT 36.5%. LDA had the highest test accuracy, reflecting the bias-variance tradeoff over the range of complexities inherent to the algorithms tested. Several algorithms were able to match the current standard in burn tissue classification, the clinical judgment of expert burn surgeons. These results will guide further development of an MSI burn tissue classification system. Given that there are few surgeons and facilities specializing in burn care, this technology may improve the standard of burn care for patients without access to specialized facilities.

A general derivation and quantification of the third law of thermodynamics.

PubMed

Masanes, Lluís; Oppenheim, Jonathan

2017-03-14

The most accepted version of the third law of thermodynamics, the unattainability principle, states that any process cannot reach absolute zero temperature in a finite number of steps and within a finite time. Here, we provide a derivation of the principle that applies to arbitrary cooling processes, even those exploiting the laws of quantum mechanics or involving an infinite-dimensional reservoir. We quantify the resources needed to cool a system to any temperature, and translate these resources into the minimal time or number of steps, by considering the notion of a thermal machine that obeys similar restrictions to universal computers. We generally find that the obtainable temperature can scale as an inverse power of the cooling time. Our results also clarify the connection between two versions of the third law (the unattainability principle and the heat theorem), and place ultimate bounds on the speed at which information can be erased.

A general derivation and quantification of the third law of thermodynamics

PubMed Central

Masanes, Lluís; Oppenheim, Jonathan

2017-01-01

The most accepted version of the third law of thermodynamics, the unattainability principle, states that any process cannot reach absolute zero temperature in a finite number of steps and within a finite time. Here, we provide a derivation of the principle that applies to arbitrary cooling processes, even those exploiting the laws of quantum mechanics or involving an infinite-dimensional reservoir. We quantify the resources needed to cool a system to any temperature, and translate these resources into the minimal time or number of steps, by considering the notion of a thermal machine that obeys similar restrictions to universal computers. We generally find that the obtainable temperature can scale as an inverse power of the cooling time. Our results also clarify the connection between two versions of the third law (the unattainability principle and the heat theorem), and place ultimate bounds on the speed at which information can be erased. PMID:28290452

Foreign Language Translation of Chemical Nomenclature by Computer

PubMed Central

2009-01-01

Chemical compound names remain the primary method for conveying molecular structures between chemists and researchers. In research articles, patents, chemical catalogues, government legislation, and textbooks, the use of IUPAC and traditional compound names is universal, despite efforts to introduce more machine-friendly representations such as identifiers and line notations. Fortunately, advances in computing power now allow chemical names to be parsed and generated (read and written) with almost the same ease as conventional connection tables. A significant complication, however, is that although the vast majority of chemistry uses English nomenclature, a significant fraction is in other languages. This complicates the task of filing and analyzing chemical patents, purchasing from compound vendors, and text mining research articles or Web pages. We describe some issues with manipulating chemical names in various languages, including British, American, German, Japanese, Chinese, Spanish, Swedish, Polish, and Hungarian, and describe the current state-of-the-art in software tools to simplify the process. PMID:19239237

A video event trigger for high frame rate, high resolution video technology

NASA Astrophysics Data System (ADS)

Williams, Glenn L.

1991-12-01

When video replaces film the digitized video data accumulates very rapidly, leading to a difficult and costly data storage problem. One solution exists for cases when the video images represent continuously repetitive 'static scenes' containing negligible activity, occasionally interrupted by short events of interest. Minutes or hours of redundant video frames can be ignored, and not stored, until activity begins. A new, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term or short term changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pretrigger and post-trigger storage techniques are then adaptable for archiving the digital stream from only the significant video images.

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

Adapter plate assembly for adjustable mounting of objects

DOEpatents

Blackburn, R.S.

1986-05-02

An adapter plate and two locking discs are together affixed to an optic table with machine screws or bolts threaded into a fixed array of internally threaded holes provided in the table surface. The adapter plate preferably has two, and preferably parallel, elongated locating slots each freely receiving a portion of one of the locking discs for secure affixation of the adapter plate to the optic table. A plurality of threaded apertures provided in the adapter plate are available to attach optical mounts or other devices onto the adapter plate in an orientation not limited by the disposition of the array of threaded holes in the table surface. An axially aligned but radially offset hole through each locking disc receives a screw that tightens onto the table, such that prior to tightening of the screw the locking disc may rotate and translate within each locating slot of the adapter plate for maximum flexibility of the orientation thereof.

Knowledge Extraction and Semantic Annotation of Text from the Encyclopedia of Life

PubMed Central

Thessen, Anne E.; Parr, Cynthia Sims

2014-01-01

Numerous digitization and ontological initiatives have focused on translating biological knowledge from narrative text to machine-readable formats. In this paper, we describe two workflows for knowledge extraction and semantic annotation of text data objects featured in an online biodiversity aggregator, the Encyclopedia of Life. One workflow tags text with DBpedia URIs based on keywords. Another workflow finds taxon names in text using GNRD for the purpose of building a species association network. Both workflows work well: the annotation workflow has an F1 Score of 0.941 and the association algorithm has an F1 Score of 0.885. Existing text annotators such as Terminizer and DBpedia Spotlight performed well, but require some optimization to be useful in the ecology and evolution domain. Important future work includes scaling up and improving accuracy through the use of distributional semantics. PMID:24594988

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.

NASTRAN internal improvements for 1992 release

NASA Technical Reports Server (NTRS)

Chan, Gordon C.

1992-01-01

The 1992 NASTRAN release incorporates a number of improvements transparent to users. The NASTRAN executable was made smaller by 70 pct. for the RISC base Unix machines by linking NASTRAN into a single program, freeing some 33 megabytes of system disc space that can be used by NASTRAN for solving larger problems. Some basic matrix operations, such as forward-backward substitution (FBS), multiply-add (MPYAD), matrix transpose, and fast eigensolution extraction routine (FEER), have been made more efficient by including new methods, new logic, new I/O techniques, and, in some cases, new subroutines. Some of the improvements provide ground work ready for system vectorization. These are finite element basic operations, and are used repeatedly in a finite element program such as NASTRAN. Any improvements on these basic operations can be translated into substantial cost and cpu time savings. NASTRAN is also discussed in various computer platforms.

Adapter plate assembly for adjustable mounting of objects

DOEpatents

Blackburn, Robert S.

1987-01-01

An adapter plate and two locking discs are together affixed to an optic table with machine screws or bolts threaded into a fixed array of internally threaded holes provided in the table surface. The adapter plate preferably has two, and preferably parallel, elongated locating slots each freely receiving a portion of one of the locking discs for secure affixation of the adapter plate to the optic table. A plurality of threaded apertures provided in the adapter plate are available to attach optical mounts or other devices onto the adapter plate in an orientation not limited by the disposition of the array of threaded holes in the table surface. An axially aligned but radially offset hole through each locking disc receives a screw that tightens onto the table, such that prior to tightening of the screw the locking disc may rotate and translate within each locating slot of the adapter plate for maximum flexibility of the orientation thereof.

Holographic acoustic elements for manipulation of levitated objects.

PubMed

Marzo, Asier; Seah, Sue Ann; Drinkwater, Bruce W; Sahoo, Deepak Ranjan; Long, Benjamin; Subramanian, Sriram

2015-10-27

Sound can levitate objects of different sizes and materials through air, water and tissue. This allows us to manipulate cells, liquids, compounds or living things without touching or contaminating them. However, acoustic levitation has required the targets to be enclosed with acoustic elements or had limited manoeuvrability. Here we optimize the phases used to drive an ultrasonic phased array and show that acoustic levitation can be employed to translate, rotate and manipulate particles using even a single-sided emitter. Furthermore, we introduce the holographic acoustic elements framework that permits the rapid generation of traps and provides a bridge between optical and acoustical trapping. Acoustic structures shaped as tweezers, twisters or bottles emerge as the optimum mechanisms for tractor beams or containerless transportation. Single-beam levitation could manipulate particles inside our body for applications in targeted drug delivery or acoustically controlled micro-machines that do not interfere with magnetic resonance imaging.

Holographic acoustic elements for manipulation of levitated objects

NASA Astrophysics Data System (ADS)

Marzo, Asier; Seah, Sue Ann; Drinkwater, Bruce W.; Sahoo, Deepak Ranjan; Long, Benjamin; Subramanian, Sriram

2015-10-01

Sound can levitate objects of different sizes and materials through air, water and tissue. This allows us to manipulate cells, liquids, compounds or living things without touching or contaminating them. However, acoustic levitation has required the targets to be enclosed with acoustic elements or had limited manoeuvrability. Here we optimize the phases used to drive an ultrasonic phased array and show that acoustic levitation can be employed to translate, rotate and manipulate particles using even a single-sided emitter. Furthermore, we introduce the holographic acoustic elements framework that permits the rapid generation of traps and provides a bridge between optical and acoustical trapping. Acoustic structures shaped as tweezers, twisters or bottles emerge as the optimum mechanisms for tractor beams or containerless transportation. Single-beam levitation could manipulate particles inside our body for applications in targeted drug delivery or acoustically controlled micro-machines that do not interfere with magnetic resonance imaging.