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On Some Methods in Safety Evaluation in Geotechnics

, European Committee for Standardization, Brussels. [18] FENTON G.A., VANMARCKE E., Simulation of random fields via local average subdivision, ASCE J. Geotech. Eng., 1990, 116(8), 1733-1749. [19] FENTON G.A, GRIFFITHS D.V., Bearing capacity prediction of spatially random c-φ soils, Canadian Geotechnical Journal, 2003, 40(1), 54-65. [20] FENTON G.A., GRIFFITHS D.V., CAVERS W., Resistance factors for settlement design, Canadian Geotechnical Journal, 2005, 42(5), 1422-1436. [21] FENTON G.A., GRIFFITHS D.V., ZHANG

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Estimation of spatial variability of lignite mine dumping ground soil properties using CPTu results

REFERENCES [1] B uczko U., G erke H.H., H üttl R.F., Spatial distributions of lignite mine spoil properties for simulating 2-D variably saturated flow and transport , Ecological Engineering, 2001, 17(2), 103–114. [2] D mitruk S., S uchnicka H., Geotechniczne zabezpieczenie wydobycia , 1976. [3] F enton G.A., G riffiths D.V., Bearing-capacity prediction of spatially random c φ soils , Canadian Geotechnical Journal, 2003, 40(1), 54–65. [4] F enton G.A., V anmarcke E.H., Simulation of random fields via local average subdivision

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Evaluation of Bearing Capacity of Strip Footing Using Random Layers Concept

References AL-BITTAR T., SOUBRA A.H., 2013, Bearing capacity of strip footings on spatially random soils using sparse polynomial chaos expansion, International Journal for Numerical and Analytical Methods in Geomechanics, 37 (13), 2039-2060. FENTON G.A., GRIFFITHS D.V., 2003, Bearing-capacity prediction of spatially random cφ soils, Canadian Geotechnical Journal, 40 (1), 54-65. FENTON G.A., VANMARCKE E.H., 1990, Simulation of random fields via local average subdivision, Journal of Engineering Mechanics, 116

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EFFECT OF RANDOM AXIAL CURVATURE OF A THIN-WALLED BEAM ON ITS LOAD-CARRYING CAPACITY

Abstract

The paper deals with the analysis of load-carrying capacity (LCC) of a thin-walled steel beam under compression the axis of which is randomly spatially curved. Open and close thin-walled crosssections are considered for the beam, respectively. The initial curvature is modelled by a random field. The Latin Hypercube Sampling Method was applied. The load carrying capacity is calculated by geometrically nonlinear solution using ANSYS software. The results are presented both in histograms and in a table. The LCC statistical characteristics of beams with open and closed crosssections have been compared. A comparison with the LCC according to the standards is carried out as well.

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High-Order Markov Random Fields and Their Applications in Cross-Language Speech Recognition

Abstract

In this paper we study the cross-language speech emotion recognition using high-order Markov random fields, especially the application in Vietnamese speech emotion recognition. First, we extract the basic speech features including pitch frequency, formant frequency and short-term intensity. Based on the low level descriptor we further construct the statistic features including maximum, minimum, mean and standard deviation. Second, we adopt the high-order Markov random fields (MRF) to optimize the cross-language speech emotion model. The dimensional restrictions may be modeled by MRF. Third, based on the Vietnamese and Chinese database we analyze the efficiency of our emotion recognition system. We adopt the dimensional emotion model (arousal-valence) to verify the efficiency of MRF configuration method. The experimental results show that the high-order Markov random fields can improve the dimensional emotion recognition in the cross-language experiments, and the configuration method shows promising robustness over different languages.

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Accounting for Contiguous Multiword Expressions in Shallow Parsing

. Sag, I. A., T. Baldwin, F. Bond, A. Copestake, and D. Flickinger. Multiword expressions: A pain in the neck for nlp. In Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing (CICLing ’02) , pages 1-15, London, UK, 2002. Springer- Verlag. Sha, F. and F. Pereira. Shallow parsing with conditional random fields. In Proceedings of the Conference on Human Language Technologies and the Annual Conference of the North American Chapter of the Association for Computational Linguistics (HLT-NAACL’03

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A Dynamic BI–Orthogonal Field Equation Approach to Efficient Bayesian Inversion

. and Sane, S. (2009). Bayesian framework for calibration of gas turbine simulator, Journal of Propulsion and Power 25(4): 987-992. Trucano, T., Swiler, L., Igusa, T., Oberkampf, W. and M., P. (2006). Calibration, validation, and sensitivity analysis: What’s what, Reliability Engineering and System Safety 91(10-11): 1331-1357. Venturi, D. (2011). A fully symmetric nonlinear biorthogonal decomposition theory for random fields, Physica D 240(4-5): 415-425. Wiener, N. (1938). The homogeneous chaos, American Journal of

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Random analysis of bearing capacity of square footing using the LAS procedure

References [1] EN 1990:2002. Eurocode: Basis of structural design. CEN, European Committee for Standardization, Brussels. [2] FENTON G.A., GRIFFITHS D.V., Bearing-capacity prediction of spatially random c φ soils, Canadian Geotechnical Journal, 2003, 40(1), 54-65. [3] FENTON G.A., GRIFFITHS D.V., Risk Assessment in Geotechnical Engineering, John Wiley & Sons, New York 2008. [4] FENTON G.A., VANMARCKE E.H., Simulation of random fields via local average subdivision, Journal of Engineering Mechanics

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Enhancing Clinical Decision Support Systems with Public Knowledge Bases

models in biomedical text retrieval task. Both Balaneshin-kordan et al. [ 8 ] and Xie et al. [ 9 ] used the Markov Random Field (MRF) model and got very high retrieval performance. Song et al. [ 10 ] proposed to retrieve relevant biomedical articles by combining three retrieval models, including BM25, PL2, and BB2, and their results performed the best in 2015 CDS task B. In the query expansion procedure of all these previous studies, it is showed that the quality of the expanded terms is important. Since the diagnosis can better reflect users’ true information needs

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Characterizing sand ripples at equilibrium phases

Abstract

Morphological characteristics of ripples are analyzed considering bed surfaces as two dimensional random fields of bed elevations. Two equilibrium phases are analyzed with respect to successive development of ripples based on digital elevation models. The key findings relate to the shape of the two dimensional second-order structure functions and multiscaling behavior revealed by higher-order structure functions. Our results suggest that (1) the two dimensional second-order structure functions can be used to differentiate the two equilibrium phases of ripples; and (2) in contrast to the elevational time series of ripples that exhibit significant multiscaling behavior, the DEMs of ripples at both equilibrium phases do not exhibit multiscaling behavior.

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