The performance of a machine translation system heavily depends on the quantity and quality of the bilingual language resource. However,getting a parallel corpus,which has a large scale and is of high quality,is a ver...
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The performance of a machine translation system heavily depends on the quantity and quality of the bilingual language resource. However,getting a parallel corpus,which has a large scale and is of high quality,is a very difficult task especially for low resource languages such as Chinese-Vietnamese. Fortunately,multilingual user generated contents( UGC),such as bilingual movie subtitles,provide us access to automatic construction of the parallel corpus. Although the amount of UGC parallel corpora can be considerable,the original corpus is not suitable for statistical machine translation( SMT) systems. The corpus may contain translation errors,sentence mismatching,free translations,etc. To improve the quality of the bilingual corpus for SMT systems,three filtering methods are proposed: sentence length difference,the semantic of sentence pairs,and machine learning. Experiments are conducted on the Chinese to Vietnamese translation *** results demonstrate that all the three methods effectively improve the corpus quality,and the machine translation performance( BLEU score) can be improved by 1. 32.
Heterogeneous clusters with multiple sockets and multicore-processors accelerated by dedicated coprocessors like GPUs, Cell BE, FPGAs or others nowadays provide unrivaled computing power in terms of floating point ope...
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We present a kinetic Monte Carlo (KMC) model for the electroplating of through silicon vias. The KMC model includes the chemical and transport properties of the copper ions, suppressors and accelerators in the electro...
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In this paper, multiresolution data visualiztion techniques are discussed, which include auto-level-switch between datasets of different resolution, rendering with adaptive resolution and interactive visualization met...
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Evidence of superconductivity (SC) has recently been reported in pressurized La3Ni2O7-δ and La4Ni3O10-δ, providing a new platform to explore high-temperature superconductivity. However, while zero resistance state h...
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Surgical video workflow analysis has made intensive development in computer-assisted surgery by combining deep learning models, aiming to enhance surgical scene analysis and decision-making. However, previous research...
Surgical video workflow analysis has made intensive development in computer-assisted surgery by combining deep learning models, aiming to enhance surgical scene analysis and decision-making. However, previous research has primarily focused on coarse-grained analysis of surgical videos, e.g., phase recognition, instrument recognition, and triplet recognition that only considers relationships within surgical triplets. In order to provide a more comprehensive fine-grained analysis of surgical videos, this work focuses on accurately identifying triplets from surgical videos. Specifically, we propose a vision-language deep learning framework that incorporates intra- and inter- triplet modeling, termed I2TM, to explore the relationships among triplets and leverage the model understanding of the entire surgical process, thereby enhancing the accuracy and robustness of recognition. Besides, we also develop a new surgical triplet semantic enhancer (TSE) to establish semantic relationships, both intra- and inter-triplets, across visual and textual modalities. Extensive experimental results on surgical video benchmark datasets demonstrate that our approach can capture finer semantics, achieve effective surgical video understanding and analysis, with potential for widespread medical applications.
The use of computational-intelligence-based techniques in the optimization of agent initial positions in land combat simulations is studied. A novel method for the reduction of support vectors in the support vector ma...
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The use of computational-intelligence-based techniques in the optimization of agent initial positions in land combat simulations is studied. A novel method for the reduction of support vectors in the support vector machine (SVM) is presented. The optimization on the width of the Gaussian kernel function and the combination of the SVM with the radial basis function neural network are performed in the proposed method. Simulation results show that the proposed method can improve the running efficiency drastically compared with that using the traditional SVM with the same precision. We also summarize and present some experiences and trends in the study on the optimization problem in land combat simulation.
We present a set of optimized passive and active photonic devices for applications in quantum photonic systems based on silicon material platforms. These devices form key parts of active integrated photonic quantum ci...
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Deepwater developments have increased the use of unbonded flexible risers as a means of transporting hydrocarbons from the wells and offloading to pipelines that convey the processed fluids to shore. The development o...
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ISBN:
(纸本)9781632663870
Deepwater developments have increased the use of unbonded flexible risers as a means of transporting hydrocarbons from the wells and offloading to pipelines that convey the processed fluids to shore. The development of improved computational models for global dynamic analysis and component stress analysis of flexible risers is required to ensure that they will perform as required over the life-time of the field. Flexible risers are slender composite structures consisting of multiple polymer layers and helically-wound steel layers with complex geometries. The global response depends on an accurate representation of the local stiffness which is influenced by the ability of the layers to slide over each other. In this work, a multi-linear model is proposed for characterising the non-linear hysteretic behaviour of flexible pipes and a procedure is demonstrated for determining the parameters of this model from bending test data or from numerical simulations. Herein, the parameters of the model are determined through processing of bending response data obtained from a detailed local finite element model of a segment of the riser. It is shown that the proposed model can reproduce the non-linear bending response of unbonded flexible risers, accounting for the effects of internal and external pressures. The model is proposed as a means of improving the global analysis accuracy and represents one of the components of a future multi-scale modelling approach for flexible pipes. Copyright 2014, Offshore technology Conference.
With the increasing popularity of shared-memory programming model, especially at the advent of Multi-Core processors, more and more programmers hope to write parallel multithread programs conveniently and effectively ...
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ISBN:
(纸本)9781595937575
With the increasing popularity of shared-memory programming model, especially at the advent of Multi-Core processors, more and more programmers hope to write parallel multithread programs conveniently and effectively with the help of parallel multithread programming interface. Unfortunately, these interfaces are not well accepted by sequential programmers, because of incomplete elimination of lower-level details, inflexibility selection of library functions, depending on specific compilers. This paper presents a unique generic object-oriented parallel multithread programming interface, which is designed and implemented to solve the drawbacks of current parallel multithread programming interfaces. Evaluation results show that programmers can benefit a lot from the interface.
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