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Language Membership Identification Precedes Semantic Access: Suppression during Bilingual Word Recognition

JOURNAL OF COGNITIVE NEUROSCIENCE 2015年第11期27卷 2108-2116页

作者： Hoversten, Liv J. Brothers, Trevor Swaab, Tamara Y. Traxler, Matthew J. Univ Calif Davis Davis CA 95616 USA

Previous research suggests that bilingual comprehenders access lexical representations of words in both languages nonselectively. However, it is unclear whether global language suppression plays a role in guiding attention to target language representations during ongoing lexico-semantic processing. To help clarify this issue, this study examined the relative timing of language membership and meaning activation during visual word recognition. Spanish-English bilinguals performed simultaneous semantic and language membership classification tasks on single words during EEG recording. Go/no-go ERP latencies provided evidence that language membership information was accessed before semantic information. Furthermore, N400 frequency effects indicated that the depth of processing of words in the nontarget language was reduced compared to the target language. These results suggest that the bilingual brain can rapidly identify the language to which a word belongs and subsequently use this information to selectively modulate the degree of processing in each language accordingly.

关键词： Semantics word recognition object oriented programming languages working depth Language Word

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Physiomodel - An Integrative Physiology in Modelica 37

Physiomodel - An Integrative Physiology in Modelica

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37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Matejak, Marek Kofranek, Jiri Charles Univ Prague Fac Med 1 Prague Czech Republic

ISBN: (纸本)9781424492701

Physiomodel (http://***) is our reimplementation and extension of an integrative physiological model called HumMod 1.6 (http://***) using our Physiolibrary (http://***). The computer language Modelica is well-suited to exactly formalize integrative physiology. Modelica is an equation-based, and object-oriented language for hybrid ordinary differential equations (http://***). Almost every physiological term can be defined as a class in this language and can be instantiated as many times as it occurs in the body. Each class has a graphical icon for use in diagrams. These diagrams are self-describing;the Modelica code generated from them is the full representation of the underlying mathematical model. Special Modelica constructs of physical connectors from Physiolibrary allow us to create diagrams that are analogies of electrical circuits with Kirchhoff's laws. As electric currents and electric potentials are connected in electrical domain, so are molar flows and concentrations in the chemical domain;volumetric flows and pressures in the hydraulic domain;flows of heat energy and temperatures in the thermal domain;and changes and amounts of members in the population domain.

关键词： Physiomodel Integrative Physiology Modelica Domain object oriented programming languages Physiology potential electric current Thermal energy Computer programming languages

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Ruby Benchmark Tool using Docker

Ruby Benchmark Tool using Docker

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Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Ludvigh, Richard Rebok, Tomas Tunka, Vaclav Nguyen, Filip Masaryk Univ Fac Informat Bot 68a Brno 60200 Czech Republic JBoss Middleware Red Hat Czech Brno 61245 Czech Republic

ISBN: (纸本)9788360810668

The purpose of this paper is to introduce and describe a new Ruby benchmarking tool. We will describe the background of Ruby benchmarking and the advantages of the new tool. The paper documents the benchmarking process as well as methods used to obtain results and run tests. To illustrate the provided tool, results that were obtained by running a developed benchmarking tool on existing and available official ruby benchmarks are provided. These results document advantages in using various Ruby compilers or Ruby implementations.

关键词： object-oriented languages program compilers Ruby benchmark tool Ruby compilers pure object-oriented interpreted language Benchmark testing Containers Linux Magnetic resonance imaging Parallel processing Servers Virtual machining compilers virtual machines Benchmark testing object oriented programming languages Servers PARALLEL PROCESSING (COMPUTERS) Ruby Linux CONTAINERS BENCHMARKS Magnetic Resonance Imaging virtual machining dockers

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Personnel Psychological Metaphor System about Time-Space Conversion in Intelligent Transportation Processes 5

Personnel Psychological Metaphor System about Time-Space Con...

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5th International Conference on Transportation Engineering, ICTE 2015

作者： Lu, Yang Chun, Guo College of Foreign Languages Southwest Jiaotong University Chengdu Sichuan China Key Laboratory of Transportation Tunnel Engineering Ministry of Education Southwest Jiaotong University Chengdu China

ISBN: (数字)9780784479384

ISBN: (纸本)9780784479384

With the development of transportation technology, increasing the degree of intelligent transportation, intelligent transportation affected staff travel is also growing. Fast time-space conversion to personnel changes have an important psychological impact, Especially in intelligent transportation area, the difference of languages and understanding ways between different countries makes a great deal of obstacles. Foreign language teaching is a second language teaching, its goal is to train students for the language skills of the target language and language communication ability. This paper established the architecture and application mode of saptio-temporal metaphor system in transportation engineering teaching internationalization process. © ASCE.

关键词： Intelligent transportation Time-space conversion Psychological metaphor Architecture Application mode Intelligent Transportation ARCHITECTURE Building construction object oriented programming languages new vehicle designs Traffic engineering Language Proficiency Metaphor changeover time Language

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Multi-lingual speech recognition with low-rank multi-task deep neural networks

Multi-lingual speech recognition with low-rank multi-task de...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： A. Mohan R. Rose Dept. of Electr. & Comput. Eng. McGill Univ. Montreal QC Canada

ISBN: (纸本)9781467369985

Multi-task learning (MTL) for deep neural network (DNN) multilingual acoustic models has been shown to be effective for learning parameters that are common or shared between multiple languages[1, 2]. In the MTL paradigm, the number of parameters in the output layer is large and scales with the number of languages used in training. This output layer becomes a computational bottleneck. For mono-lingual DNNs, low-rank matrix factorization (LRMF) of weight matrices have yielded large computational savings[3, 4]. The LRMF proposed in this work for MTL, is for the original languagespecific block matrices to "share" a common matrix, with resulting low-rank language specific block matrices. The impact of LRMF is presented in two scenarios, namely : (a) improving performance in a target language when auxiliary languages are included during multi-lingual training;and (b) cross-language transfer to an unseen language with only 1 hour of transcribed training data. A 44% parameter reduction in the final layer, manifests itself in providing a lower memory footprint and faster training times. An experimental study shows that the LRMF multi-lingual DNN provides competitive performance compared to a full-rank multi-lingual DNN in both scenarios.

关键词： Low-resource speech recognition Multi-lingual speech recognition Multitask Learning Neural Networks for speech recognition Language object oriented programming languages Speech recognition matrices partitioned matrix Neural network Functional training Acoustic models

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Context-extended phrase reordering model for pivot-based statistical machine translation

Context-extended phrase reordering model for pivot-based sta...

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International Conference on Asian Language Processing (IALP)

作者： Xiaoning Zhu Tiejun Zhao Yiming Cui Conghui Zhu School of Computer Science and Technology Harbin Institute of Technology Harbin China Harbin Institute of Technology Harbin Heilongjiang CN

For translation between language pairs which is lack of bilingual data, pivot-based SMT uses a pivot language as a “bridge” to generate source-target translation, inducing from source-pivot and pivot-target translation. However, due to the missing of the context information, the reordering model was hard to obtain with the conventional methods. In this paper, we present a context-extended phrase reordering model for pivot-based statistical machine translation by extending the context information in source, pivot and target language. Experimental results show that our method leads to significant improvements over the baseline system on European Parliament data.

关键词： context machine translation pivot reordering machine translation Pivot Device Component REORDERING object oriented programming languages

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Topic-Based Dissimilarity and Sensitivity Models for Translation Rule Selection

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JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH 2014年第1期50卷 1-30页

作者： Zhang, Min Xiao, Xinyan Xiong, Deyi Liu, Qun Soochow Univ Prov Key Lab Comp Informat Proc Technol Suzhou Peoples R China Chinese Acad Sci Inst Comp Technol IIP Key Lab Beijing 100864 Peoples R China Dublin City Univ Sch Comp CNGL Dublin 9 Ireland

Translation rule selection is a task of selecting appropriate translation rules for an ambiguous source-language segment. As translation ambiguities are pervasive in statistical machine translation, we introduce two topic-based models for translation rule selection which incorporates global topic information into translation disambiguation. We associate each synchronous translation rule with source- and target-side topic distributions. With these topic distributions, we propose a topic dissimilarity model to select desirable (less dissimilar) rules by imposing penalties for rules with a large value of dissimilarity of their topic distributions to those of given documents. In order to encourage the use of non-topic specific translation rules, we also present a topic sensitivity model to balance translation rule selection between generic rules and topic-specific rules. Furthermore, we project target-side topic distributions onto the source- side topic model space so that we can benefit from topic information of both the source and target language. We integrate the proposed topic dissimilarity and sensitivity model into hierarchical phrase-based machine translation for synchronous translation rule selection. Experiments show that our topic-based translation rule selection model can substantially improve translation quality.

关键词： Rule machine translation object oriented programming languages reduced mass

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A Comparative Study of Bug Patterns in Java Cloned and Non-cloned Code 14

A Comparative Study of Bug Patterns in Java Cloned and Non-c...

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14th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM)

作者： Sajnani, Hitesh Saini, Vaibhav Lopes, Cristina V. Univ Calif Irvine Bren Sch Informat & Comp Sci Irvine CA 92697 USA

ISBN: (纸本)9780769553047

Code cloning via copy-and-paste is a common practice in software engineering. Traditionally, this practice has been considered harmful, and a symptom that some important design abstraction is being ignored. As such, many previous studies suggest approaches to facilitate the discovery, removal, and refactoring of clones. However, not many studies exist that empirically investigate the relationship of code clones with code quality. In this paper, we conduct an empirical study of 31 open source Java projects (1.7 MSLOC) to explore the relationship between code clones and a set of bug patterns reported by FindBugs. We found that: (i) the defect density in cloned code is 3.7 times less than that of the rest of the code;(ii) 66% of the bug patterns associated with code clones are related to issues in coding style and practice, the two least problematic of the FindBugs categories, while that number is 49% for non-cloned code;and (iii) 75% of the bug patterns in cloned code are duplicated without any changes, while 25% are only present in one of the clones. These results show that, when using FindBugs to detect bug patterns, there is a positive differentiation of cloned code with respect to the rest of the code: the cloned code has considerably less, and less problematic, bug patterns. While our study does not unveil any explanation for this, results from other, more qualitative studies indicate that developers use copy-and-paste intentionally and wisely, which may explain the quantitative observations of our study. Overall, these research results suggest that the practice of code cloning in Java, and possibly in all other object-oriented languages, needs to be given serious consideration on the part of tool designers.

关键词： Java program debugging public domain software software quality source code (software) Java cloned code Java noncloned code bug pattern detection code quality copy-and-paste defect density design abstraction find bugs category object-oriented languages open source Java projects software engineering Cloning Computer bugs Correlation Encoding Google Software bug patterns code clones Java Java programming language bugs Codes object oriented programming languages open source software Debugging Software engineering software quality Bugs Cloning computer software

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Principles of an object-oriented programming Language for Physarum Polycephalum Computing

Principles of an Object-Oriented Programming Language for Ph...

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10th International Conference on Digital Technologies

作者： Pancerz, Krzysztof Schumann, Andrew Univ Informat Technol & Management Rzeszow Poland

ISBN: (纸本)9781479933037

In the paper, we present principles of an object-oriented programming language for Physarum polycephalum computing. Physarum polycephalum is a one-cell organism that can be used for developing a biological architecture of different abstract devices. Both, theoretical foundations and assumptions for a language specification are considered. Especially, we focus on selected approaches (ladder diagrams, Petri nets, and transition systems) enabling us to model behaviour of Physarum polycephalum in the created programming language.

关键词： Physarum polycephalum object oriented programming languages Language specification Principle-Based Ethics Petri nets cells by organism

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Cross-language Transfer Speech Recognition using Deep Learning

Cross-language Transfer Speech Recognition using Deep Learni...

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11th IEEE International Conference on Control and Automation (ICCA)

作者： Zhao, Yue Xu, Yan M. Sun, Mei J. Xu, Xiao N. Wang, Hui Yang, Guo S. Ji, Qiang Minzu Univ China Dept Automat Beijing 100081 Peoples R China China Ship Res & Dev Acad Beijing 100192 Peoples R China Minzu Univ China Sch Informat Engn Beijing 100081 Peoples R China Rensselaer Polytech Inst Dept Elect Comp & Syst Engn Troy NY 12180 USA

ISBN: (纸本)9781479928378

Cross-language transfer speech recognition aims to transform phoneme models for a source language to recognize a target language lacking labeled data and other linguistic resources. In this paper, sparse auto-encoder, a deep learning method, is introduced to derive shared speech features between source and target language using semi-supervised learning. It can extract the shared representation of phonemes between the source and target languages so that the target phones can be mapped to the appropriate phones of the source languages. The experimental results showed this method performs better on cross-language phones recognition than the method based on multilayer perceptron.

关键词： Data models Encyclopedias Feature extraction Hidden Markov models Speech Speech recognition Target recognition Encyclopedias Speech recognition Target recognition data models Hidden Markov models original language object oriented programming languages Feature extraction Speech Telephone Machine Learning Phonemes

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