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Applying Monte Carlo Techniques to Language Identification [chapter]

Arjen Poutsma
Computational Linguistics in the Netherlands 2001  
To avoid this, we introduce a new language identification technique that is based on Monte Carlo sampling.  ...  We describe the best-known modeling and classification techniques known in literature, and identify one disadvantage in them: the need to create a model of the entire document, even though the language  ...  Method This subsection describes the statistical method used in the Monte Carlo language identification technique.  ... 
doi:10.1163/9789004334038_015 fatcat:td2ryjgwgvfp3otfy7zoj5r72y

The Network Solution For Electron Identification in a Wide Momentum Region with a TRD [article]

N. Kuropatkin
1998 arXiv   pre-print
Both parts are built using the object oriented technique and C++ language. The particle identification algorithm is wrapped in FORTRAN closers to be used in the E781 off-line program.  ...  The package performance was tested in comparison with the likelihood ratio method using Monte Carlo generated data.  ...  In the following we describe and discuss the maximum likelihood ratio technique, our ANN approach and compare their performance with Monte Carlo simulated data.  ... 
arXiv:physics/9811039v1 fatcat:zifxcgfp7vhgjiw66v5dwxhgyu

Page 151 of Computational Linguistics Vol. 29, Issue 1 [page]

2003 Computational Linguistics  
Monte Carlo techniques to language identification” by Arjen Poutsma “Automated compounding as a means for maximizing lexical coverage” by Vincent Vandeghinste  ...  grammar: A declarative definition” by Gerard Kempen and Karin Harbusch “Multi-feature error detection in spoken dialogue systems” by Piroska Lendvai, Antal van den Bosch, Emiel Krahmer, and Marc Swerts “Applying  ... 

Page 2087 of Psychological Abstracts Vol. 88, Issue 6 [page]

2001 Psychological Abstracts  
Yet, there is little guidance for the re- searcher interested in using the technique. In this article we illustrate both the design and implementation of Monte Carlo simulations.  ...  Throughout the article, we use as a running example a Monte Carlo simulation that we performed to illustrate many of the relevant points with concrete information and detail.  ... 

Identifying Uncertainty in Environmental Risk Assessments: The Development of a Novel Typology and Its Implications for Risk Characterization

Daniel J. C. Skinner, Sophie A. Rocks, Simon J. T. Pollard, Gillian H. Drew
2014 Human and Ecological Risk Assessment  
The conceptual Refers to probability density functions that are applied independently of the Monte-Carlo simulation and Latin-hypercube sampling techniques.  ...  Uncertainty management technique Description Associated uncertainty locations Referenced in: Monte-Carlo simulation (22.1%) Utilises repeated executions of numerical models to simulate  ... 
doi:10.1080/10807039.2013.779899 fatcat:txggyo27ubfqxdkse7twudzzjm

Approximating object based architecture for legacy software written in procedural languages using Variable Neighborhood Search

Md. Selim, Md. Saeed Siddik, Tajkia Rahman, Alim Ul Gias, Shah Mostafa Khaled
2014 The 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014)  
Legacy software, often written in procedural languages, could be a major concern for organizations due to low maintainability.  ...  The proposed algorithm was implemented and its performance was compared with state of the art techniques.  ...  Existing approaches cannot be applied to all procedural languages.  ... 
doi:10.1109/skima.2014.7083558 fatcat:sk7j7o63rbcxjittpkzlg4b4zq

Parameter Identification of the 2-Chlorophenol Oxidation Model Using Improved Differential Search Algorithm

Guang-zhou Chen, Jia-quan Wang, Ru-zhong Li
2015 Journal of Chemistry  
This paper firstly carried out the sensitivity analysis of the 2-chlorophenol oxidation model in supercritical water using the Monte Carlo method.  ...  Then, to address the nonlinearity of the model, two improved differential search (DS) algorithms were proposed to carry out the parameter identification of the model.  ...  In view of the problem that system identification techniques are often limited to linear systems and are subject to many statistical assumptions, MCAT uses the Monte Carlo simulation approach to solve  ... 
doi:10.1155/2015/313105 fatcat:mp3obrwp3balfczx5igmr4o5ea

OBJECT TRACKING BASED ON BAYESIAN MONTE CARLO EMPLOYING PARTICLE GAUSSIAN INFORMATION FILTER

K.Saravanan, P. Hima Bindu
2020 Zenodo  
Then, Monte Carlo Particle State Estimator algorithm is emp [...]  ...  In order to solve the above problems, Bayesian Monte Carlo employing Particle Gaussian Information Filter scheme is proposed for object tracking to increase the accuracy for tracking the object.  ...  Then, applied Monte Carlo Particle State Estimator algorithm is used to successfully track the single moving object in the presence of occlusion with improved accuracy.  ... 
doi:10.5281/zenodo.3708741 fatcat:dtswwfgthzeizfr2fmm2hdfy3a

Unbiased Monte Carlo for the age of tensor networks [article]

Andrew J. Ferris
2015 arXiv   pre-print
A new unbiased Monte Carlo technique called Tensor Network Monte Carlo (TNMC) is introduced based on sampling all possible renormalizations (or course-grainings) of tensor networks, in this case matrix-product  ...  The method is quite general and can be combined with a variety of tensor renormalization techniques appropriate to different geometries and dimensionalities.  ...  However, it should be kept in mind that the core of the Monte Carlo sampling algorithm can easily be applied to more advanced tensor network renormalization schemes, and that the techniques can be applied  ... 
arXiv:1507.00767v1 fatcat:kq3goq6arvhwzee6sadniji7fy

Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approach

G. Zhou, T. Esaki, Y. Mitani, M. Xie, J. Mori
2003 Engineering Geology  
Spatial probabilistic modeling of slope failure using a combined Geographic Information System (GIS), infinite-slope stability model and Monte Carlo simulation approach is proposed and applied in the landslide-prone  ...  Finally, by integrating an infinite-slope stability model and Monte Carlo simulation with GIS, and applying spatial processing, a slope failure probability distribution map is obtained for the case of  ...  Bijan Khazai (University of California at Berkeley, USA) for their valuable comments both in language and research.  ... 
doi:10.1016/s0013-7952(02)00241-7 fatcat:fmcaxzdsifab3gh6pgdirrt4su

EMPIRICAL APPROACH TO VALIDATE HEURISTIC ALGORITHMS FOR PROCEDURAL PROGRAMMING TO OBJECT ORIENTED DESIGN MIGRATION

Md Samsuddoha, MdSaeed Siddik, Md Selim, ShahMostafa Khaled
2017 International Journal of Advanced Research  
Several heuristics algorithms are proposed for migration based on Monte Carlo and Greedy [4] , Genetic Algorithm (GA) [5] , Local Search (LS) [6] , Variable Neighborhood Search (VNS) [7] and Build  ...  This research intends to make an empirical evaluation of design  ...  Most of the experiments were done on COBOL language [10] . However, procedural systems greatly differ from one another. Existing approaches cannot be applied to all procedural languages.  ... 
doi:10.21474/ijar01/5298 fatcat:xvc2dautlzgrpkji3sen5okx5q

Monte Carlo simulations in SPET and PET

I Buvat, I Castiglioni
2002 The quarterly journal of nuclear medicine : official publication of the Italian Association of Nuclear Medicine (AIMN) [and] the International Association of Radiopharmacology (IAR)  
To help potential Monte Carlo users choose a code, we present advantages and disadvantages of the different types of Monte Carlo codes currently available for SPET and PET, discuss common and specific  ...  Monte Carlo methods are extensively used in Nuclear Medicine to tackle a variety of problems that are difficult to study by an experimental or analytical approach.  ...  the Monte Carlo casino was the most famous centre for playing games involving random drawing) was applied to nuclear physics.  ... 
pmid:12072845 fatcat:zur2uks44zflnjvenuavbi4vpm

PRISM: A Tool for Automatic Verification of Probabilistic Systems [chapter]

Andrew Hinton, Marta Kwiatkowska, Gethin Norman, David Parker
2006 Lecture Notes in Computer Science  
Major additions include facilities to manually explore models, Monte-Carlo discrete-event simulation techniques for approximate model analysis (including support for distributed simulation) and the ability  ...  to compute cost-and reward-based measures, e.g.  ...  PRISM is a probabilistic model checking tool which has already been used to apply these techniques to a large and diverse set of case studies.  ... 
doi:10.1007/11691372_29 fatcat:qksgy2exbnhnfao2vxq75l6j5q

Monte Carlo Simulations on SIMD Computer Architectures

C. P. Burmester, L. T. Wille, R. Gronsky
1992 Materials Research Society Symposium Proceedings  
Each processing ele-MONTE CARLO SIMULATION IN MATERIAL,S SCIENCE The Monte Carlo simulation technique was first introduced by Meu'opolis et al. to study tile equilibrium properties of model systems 3.  ...  In what follows, general methods of developing parallel algorithms are applied to the Monte Carlo simulation of the Ising model for each of the above three cases.  ... 
doi:10.1557/proc-278-3 fatcat:obgssvuou5b65lxmys3wxuyta4

Metamorphic Testing for Machine Translations: MT4MT

Zhi Quan Zhou, Liqun Sun
2018 2018 25th Australasian Software Engineering Conference (ASWEC)  
To alleviate these problems, we have been using a metamorphic testing technique to test machine translation services in a fully automatic way without the involvement of any human assessor or reference  ...  To alleviate these problems, we have been using a metamorphic testing technique to test machine translation services in a fully automatic way without the involvement of any human assessor or reference  ...  We would like to thank Suzhou Insight Cloud Information Technology Co., Ltd for supporting this research.  ... 
doi:10.1109/aswec.2018.00021 dblp:conf/aswec/ZhouS18 fatcat:o6t2xuqn3vccvnrsqrx75x4cae
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